The following is an article I wrote and submitted to several academic library journals, who all rejected it without review. I think it's a valuable contribution to the conversation around libraries on the web, and the last article that everyone rejected seemed to strike a chord with folks. Enjoy.

In 2017, I received an email asking me to add a link to one of my library's LibGuides. It was not the first email to ask, but it was the strangest I had received. I am reproducing the email here in full:

Hello there, How are you? I hope I'm not being a bother, but my daughter, Dakota, wanted to reach out to you about your web page, Grand Valley State University Libraries Style Guide. Your page has great information that we were able to explore and use for her HTML website compilation. :)

During the school year, Dakota and I, like to do fun mother/daughter projects. This is a great way to help Dakota brush up on her HTML as well. (Which, in my opinion is great to have knowledge of!) Anywho! While googling for some more resources, Dakota found this informational HTML guide - https://www.marcaria.com/ws/en/articles/learn-about-domains-and-html. She was thinking that it'd be a valuable resource for your page. Do you mind adding it? I know she'd be delighted to make a valuable contribution and maybe help educate others as well.

Looking forward to hearing back, Mrs. Lowe (Lowe, personal communication, April 3, 2017).

The story in the email seemed implausible. I suspected "Mrs. Lowe" was connected to the content hosted on marcaria.com and did not dare come out and ask for a link. I chased down registrar information for both the site she suggested and from the URL her email came from. The website at her custom domain had been designed to look like a teacher's website, and I learned that it had been a website for a teacher a few years before but had lapsed and been purchased by another owner. I never was able to identify exactly what was going on, but it led to another question for me: why would someone go through all the trouble of creating a fake website and identity, and lying about their motives, just to get a link on my LibGuides site? I had received many requests in the past that were straightforward link requests.

For the next 5 years, I collected all the email solicitations that were sent to me and asked the liaison librarians at my institution to send me any links they received for their LibGuides. I also worked with our User Experience team, who manage our service desks and public spaces, to assign any solicitations that come through our library email into our LibAnswers ticketing queue to me. In all, I collected over 200 solicitations asking us to add links to our LibGuides. In addition to analyzing these emails, I began responding to each with a simple statement: "We do not accept unsolicited links on our website." I also began looking into the reasons we were receiving these requests, which turned out to be Search Engine Optimization (SEO). This article will walk through what I learned about SEO, link solicitations, and LibGuides in particular. It also offers suggestions on how to handle these requests.

The Importance of SERPs: Search Engine Result Page Rankings

Most websites' primary goal is getting users to visit the site. Perhaps the site needs visitors to show advertisements and bring in ad revenue. Other sites sell products and want as many visitors as possible to increase the "conversion rate" between visitors and customers. One of the most lucrative ways to drive traffic to your website is through being in the top few results on a Search Engine Result Page (SERP). Unlike ads, ranking high on a SERP is not (directly) a function of your marketing budget. You can't simply pay Google to rank number one for a particular keyword search. Google and other search engines differentiate clicks on paid ads from clicks on "organic" results—that is, results from the keyword search that are unpaid. Google and others use the metaphor of "organic" results to imply that they are "natural" and therefore unmanipulated¹. According to Ziakis et al (2019), "a website nowadays has to be indexed into the first page of SERPs in order to receive a sufficient amount of organic visitors" (p. 2). That is, if you are not on the first SERP, you're not going to get many visitors coming from search. In fact, analysis by Dean showed that the top result on a Google results page generated over a quarter of the clicks (27.6%) for a search. The top three results account together for over half of all clicks. Less than 1% of all searchers visited the second page of results (2022).

Since the early days of Google, one of the features that set it aside from other search engines is how it ranks results. PageRank, the core of Google's search algorithm, was designed to mimic academic citations. As Brin and Page (2012) spell out in their paper announcing Google, in their search engine "Academic citation literature has been applied to the web, largely by counting citations or backlinks to a given page" (p. 3827). Zhang and Cabage (2017) explain that Google "looks for links from other quality sites ... to determine the significance of a website" (p. 149). The more quality sites that link to your site, the higher you will rank in Google's SERPs. Paddy Moogan simplifies it even further by explaining linking to another website as “…effectively saying it is a good resource. Otherwise, they wouldn't link to it, much in the same way that you wouldn't send a friend to a bad restaurant.” In SEO terms, these reference links are called "Inbound links," or more commonly "backlinks." Although the actual workings of PageRank are not publicly known, SEO experts have determined that "the quality and quantity of backlinks is one of the most important factors for optimal ranking" (Ziakis et al, 2019, p.7).

When your revenue is dependent on visits to your site, then where you rank in particular keyword searches becomes vitally important. But how to change your result ranking for those keyword searches? As Barlow (2011) notes, top sites already enjoy the majority of visits from SERPs, which only solidifies their position at the top. But Killoran (2013) notes that results pages are not only a result of the interaction between search engines and searchers. Rather, “rankings are directly and indirectly shaped by the three classes of interdependent participants … search engine companies and programmers, ...webmasters and SEO practitioners, ... [and] search engine users." (p. 53). SEO experts, then, are also involved in shaping what SERPs show us.

Search Engine Optimization

I have been a Web Librarian for a decade and a half and haven't thought about Search Engine Optimization that whole time. Because academic libraries, where I work, hold research materials for the university or college community, we are not necessarily looking to grow our audience. In order to use our services, you might have to be an enrolled student, or a current staff or faculty member. Most of our licensed materials are accessible only with a current username and password, so we're not worried about attracting other, non-affiliated users². This explains why it took me so long to realize why we were being inundated with requests to put links on our website. SEO wasn't on my radar. What's more, there is not a robust body of academic literature on SEO that I might have encountered in my research.

But for websites that rely on traffic to generate revenue, SEO is a core part of everyday business. Zhang and Cabage note that "good SEO practice can increase a website's natural search engine ranking, and drive more traffic to a website—more traffic means more potential revenue from advertisement and/or affiliate for content-rich websites" (p. 159). An entire industry of consultants who track the changes and behaviors of search engines exists to help websites of all sizes. In 2021, SEO industry revenue topped 52 billion dollars, according to SEO.co (2022). This is not a small sector of the internet, but a core part of digital marketing. When Google launched in 1998, the founders believed that good content would rank on its own, by generating interest and backlinks as others recognized its quality (Sergey and Brin, 2012, p. 3827). But with the incredible growth of the web into every aspect of our lives over the past two and a half decades, this idea seems preposterous. Nevertheless, Google continues to lead with this idea, stating in its SEO Starter Guide "Creating compelling and useful content will likely influence your website more than any of the other factors discussed here. Users know good content when they see it and will likely want to direct other users to it." (Optimize your content section, n.d.). But Zhang and Cabage (2017) note that "websites that rank well in search results depend upon ... a little push in the right direction, helping the website to build some momentum" (p. 149). That push is SEO.

Since Google does not share how PageRank and its associated search algorithms work, there is a lot of gray area in improving search result positioning. SEO experts generally divide techniques into two categories: white hat and black hat. White hat strategies “pose the least amount of risk and are very unlikely to lead to you being hit with a penalty from Google” (Moogan, Types of links). Conversely, black hat techniques are those that violate search engine guidelines. Killoran (2013) succinctly describes these as “deceptive SEO tactics that seek to game the ranking system” (p. 52). Of course, white hat techniques are not without risk—the strategies are those that are either explicitly permitted by the search engines or those that “pose the least amount of risk.” This hints at a third category of SEO practice, "Gray hat," or those techniques that skirt the lines between explicitly white hat techniques and black hat. And as we will see, even those techniques that are considered "white hat," like asking for links, can venture quickly into suspect territory. Mrs. Lowe, who I quoted at the beginning of this article, is an example of a white hat technique (asking for a link) that may be considered black hat and penalized by search engines if it came to light that the website was lying to get links.

Link Building

There are effectively three main white hat SEO strategies: writing quality content that uses search keywords; social sharing on Facebook, Twitter, Instagram, and other social sites; and link building (Zhang and Cabage, 2017, p. 148). Link building is the process of obtaining backlinks, of getting other sites to link to your site. Swanson (2019) notes that "link building is an essential component of any [SEO] program. In order to rank well ... it's important to have a high number of links from other websites.” The importance of link building is backed up according to a study by Zhang and Cabage (2017): "link building has the best ROI [return on investment] of any SEO strategy" (p. 159). Finding the most relevant sites to get backlinks from is considered a reflection on your own site, and not just a way to generate revenue. The SEO firm AZ Big Media claims, "link building is branding" (How to get edu backlinks, 2021).

The most common form of link building is manual outreach. This is where SEO consultants email bloggers, webmasters, (and librarians) asking to have links added to a particular website. (According to Google's SEO guidelines, sites that directly buy links will be penalized (Spam policies, n.d.), so you must pay an SEO consultant to ask for the link, rather than pay for the link directly.) This is labor intensive, but an entire software industry has risen to help SEO experts keep track of their link building efforts, which explains why there are always follow-up emails from these folks asking if we've had a chance to look over the link they sent! SEO expert Brian Dean runs regular reviews of the "top link building tools"—at the end of 2021 he reviewed 14 different software suites that would help in your link building campaigns (2021). I point this out to emphasize how big and organized this field of work is, and how essential to the daily business of most web-based sites. These are not random people emailing you to tell you about their favorite link (or one their daughter found useful while doing homework). These emails are coming from professionals who get paid to track down authoritative, quality websites across the web that are relevant to their clients' content or products and get backlinks.

.edu Backlinks

There are a few reasons that Universities get so many emails asking for backlinks—first, Google factors in the age of a domain (URL) in assigning authority, and most colleges and universities have had their domains longer than almost any other website. (The Web was created by academics, after all.) Another factor is that there is a perception that Google values educational (.edu) and government (.gov) links above other types of domains. According to one SEO website, "Edu backlinks have more trust signals than other types of websites from the eyes of search engines" (How to get edu backlinks, 2021). Because of PageRank the authority of sites that link to yours is important. According to Google's SEO Starter Guide: “You can confer some of your site's reputation to another site when your site links to it” (Use links wisely section). According to SEO thinking, getting an .edu site to link to you will help to confer those "trust signals.” Stephen Hockman (2022) argues that "if you can build a link on an EDU web page that also has high page authority with incoming links, then it can pass some of that PageRank to your website to help increase its rankings in search engines."

Despite the common thought that .edu links are valuable, Google has hinted at times that this is not true. Google "evangelist" John Mu tweeted back in 2018, "Because of the misconception that .edu links are more valuable, these sites get link-spammed quite a bit, and because of that, we [Google] ignore a ton of the links on those sites." (2018a). SEO specialist Nathan Veenstra asked to clarify: "you are actually saying that .edu (as well as .gov) links are equally valuable as links from other domains?" (2018). To which Mu replied, "are you suggesting they should be valued less given how many spammy links people place there?" (2018b). Because Google does not provide specific clarity on how its ranking algorithms work, the assumptions of SEO consultants continue to hold sway. Five years later, SEO guides continue to promote the importance of getting .edu links for SEO link builders.

Many of these guides are in the form of "listicles," or lists of techniques for getting these coveted backlinks. These articles all suggest similar techniques that they assure you are white hat, although some seem questionable. For instance, one recommendation is to ask local Universities to add your website to a local business page (if they have one), which will confer the perceived .edu magic onto your site (Portent, 2012). Another suggestion is to “reach out to [faculty] and ask if they'll be willing to collaborate with your brand to produce an interesting piece on a subject” (How to get edu backlinks, 2021), which the University will want to publicize. Almost immediately, however, the line between "paying for links" and white hat SEO techniques becomes blurred. Hiring University graduates and asking the career center to post about the hire (Portent), as well as creating scholarships (Portent, 2012; How to get edu backlinks, 2021) are common suggestions. While you are not paying the university directly to add a link to their site, offering the same money to the to a student in the form of a scholarship or job for the express purpose of getting a link on the site appears to be paying for links. Thankfully, all these articles point out that by far the easiest way to get a link is to create a resource for our favorite group of university employees: library staff.

Library Back Links and LibGuides

Shortly after hearing from "Mrs. Lowe," I began reaching out to colleagues at other institutions to see how widespread this issue was. Shelley Gullikson of Carleton University asked her colleagues about the spam requests they get for their guides. Most received a very modest amount, 1-4 a semester (personal correspondence, February 18, 2018). She mentioned that most seemed to just delete the requests without acting on them. In 2019, former University of Minnesota Librarian Franklin Sayre started a Twitter thread asking about these link solicitations. The discussion focused on numbers of requests for different disciplines and different institutions. While everyone admitted to receiving them, some got a lot while others got few or had stopped getting them at all. Sayre seemed baffled that anyone would consider adding a link, noting that he "searched site:libguides.com and it looks like others do [add links from link builders]?!?!?!?" (Sayre, 2019a). He also guessed (correctly) that while he "[didn't] know exactly what they're doing it's probably an SEO thing" (Sayre, 2019b) We have seen that SEO link builders see .edu links as having a special kind of "trust signal," and they give out specific techniques for adding links. But they also target libraries specifically, because getting links on library websites is considered easier than other areas of a university website.

In its SEO training guides, Portent (2012) recommends "chat[ting] up a librarian", while Hockman (2022) thinks you should "befriend a librarian." AZ Big Media's guide says you should “publish academic work for library guides” (How to get edu backlinks, 2021). All SEO guides agree, though, that while "librarians couldn't care less about SEO, ... they all want to ensure they're offering valuable, correct information" (Portent, 2012). Hockman (2022) says more than he writes when he points out that "Academic libraries typically have their own sections on a .edu website or have an entirely separate sub-domain of their own. This means that the content is often managed by the library staff and not the college or university's IT department. This also means it's much easier to get a high quality dollow [sic] .edu backlink for your website". Reading between the lines here, we can see that SEO folks think librarians will post any link if we think it might help people!

There are many ways SEO guides suggest going about asking libraries for backlinks. One common method, that you may have encountered, is to search for broken links on a LibGuide and then email the guide author pointing out the link is broken and, of course, asking that your link be added instead. Of course, the guides are careful to make it seem like this is a boon to libraries—"if you find a broken link on the page, help them out!" (Portent, 2012). This is a useful method for library websites, particularly LibGuides, which are often collections of loosely organized links to external websites. We use a website quality control tool called Silktide to help scan our website and LibGuides for broken links. In 2022 alone, our roughly 400 guides (over 1,900 pages) had more than 2,400 broken links over the course of the year. That seems ample opportunity for SEO link builders to find broken links and have an opportunity to "help you" with their own. Moz's own Beginner Guide to Link Building touts the benefits of “Broken link building,” and even uses a university resource guide as their example!

A university in your area happens to have an older page on dairy resources, but many of the links are broken. You kindly reach out to the webmaster to point out the broken links, and helpfully suggest your newer and up-to-date resource as an alternative. The university webmaster then links to your dairy resource page (Moogan, Link Building Tactics, n.d.)

Anderson recommends looking for "resource" pages, because "you don't need to twist anyone's arm—just reach out and politely request that they add the link" (2021). Back in 2012, Portent was already recommending that link builders use Google to hunt down LibGuides, which were referred to by name and described as "research guides on every topic imaginable." To find a LibGuide, they recommend "an 'inurl' search for 'libguides' or 'libraryguides' with a keyword." Anderson recommends searching the university with 'site:University.edu' and adding 'inurl:lib' to find the library and LibGuides all at once (2021). AZ Big Media's helps with search syntax, saying “look for available library guides from universties [sic] by using the search phrase, 'site:.edu 'libguide' 'topic' (How to get edu backlinks, 2021).

While these SEO training guides present themselves as do-gooders helping the library provide useful content to their users, the real reason for approaching libraries is two-fold: first, we are seen as an easy way to get a high-quality backlink from a .edu site. And second, an SEO link builder's goal is to make their clients money by increasing traffic to the client's site through higher SERP placement. While you may be tempted to add a resource because it does contain some valuable information, remember that the content was created with the express purpose of making money off library users. In one training guide, link builders are instructed to look for the library website and guides first, to see what kind of content the library links to. “Once you've found some libguides pages from university sites, you'll figure out what content ideas they link out to. From here, you start your outlining of content to match it to topics this libguides [sic] reference the most” (How to get edu backlinks, 2021). Beginner guide to link building points out that “sometimes you use your existing content as a suggestion … other times you create content specifically for this purpose” (Moogan, Link Building Tactics, n.d.). The pages that SEO link builders want us to link to our tailored to the content we already have! Moz's This is the clearest indication that quality content is not the main goal of SEO, backlinks, SERP placement, and revenue are.

Your library has probably received at least one email this week asking you to place a link on your LibGuides. These emails come fast and furious, sometimes to the general library email, sometimes to the Web Librarian, and sometimes to the guide owner. While they portray themselves as helpful researchers aiming to make life easier for you and your users, they are marketing professionals whose only goal is to make money for their clients by redirecting library guide traffic to their websites. Even if your users never click on their link in your LibGuide, Google (and other search engines) are perceived to give additional weight to .edu URLs that link to a particular site. Since libraries are short-staffed with ever-shrinking budgets, it may seem like an easy way to help your users by adding these links. It is not. It's a handout to the clients of SEO firms, another way for corporations to profit off the hidden labor of academic workers.

Notes

1. See, for instance, Google's claims that their results are "never manipulated" and are ranked “objectively” in their famous "Ten Things we Know to be True" document (n.d.). Unfortunately, the idea that search results are objective in any way has been picked apart sufficiently in recent years (c.f. Noble, 2018; Reidsma, 2019). In addition, Jobin and Ziewitz (2018) call into question the metaphorical distinction between "organic" and "non-organic" results by noting that "Any search results page is a carefully constructed product of design and use. There is nothing inherently 'organic' about a list of computationally generated links. ... As a metaphor, 'organic search' provides a focal point for ordering an entire field of social, economic, and political practice."↩
2. This is an oversimplification of the situation—plenty of academic libraries do want to reach users outside their institutional user base, particularly Special Collections and Archives. And Public Libraries are always looking for ways to better reach their users, who may not be aware of the range of services offered. But in both cases, there is still little traction with SEO because of the difficulties libraries face everywhere: lack of budget, staff, and training. ↩

References

Anderson, A. (2021, November 19). How to scrape Google search results for free. Linkpitch.io. https://linkpitch.io/scrape-google-search-results/

Barlow, J. (2011, May 9). What Bruce Springsteen taught me about SEO. The Coffee House Wordsmith. http://web.archive.org/web/20110612234247/http://www.coffeehousewordsmith.com/2011/05/what-bruce-springsteen-taught-me-about.html

Brin, S., & Page, L. (2012). Reprint of: The anatomy of a large-scale hypertextual web search engine. Computer Networks, 56(18), pp. 3825-3833. https://doi.org/10.1016/j.comnet.2012.10.007

Dean, B. (2021, November 2). 14 awesome link building tools [2022 reviews]. Backlink.io. https://backlinko.com/link-building-tools

Dean, B. (2022, October 14, 2022). We analyzed 4 million Google search results: Here's what we learned about organic click through rate. Backlink.io. https://backlinko.com/google-ctr-stats

Google. (n.d.) Search engine optimization (SEO) starter guide. Google Search Central. https://developers.google.com/search/docs/fundamentals/seo-starter-guide?visit_id=638156992799821424-1167987392&rd=1

Google. (n.d.) Spam policies for Google web search. https://developers.google.com/search/docs/essentials/spam-policies

Google. (n.d.) Ten things we know to be true. https://about.google/philosophy

Hockman, S. (2022, March 3). How to get .edu backlinks (15 ways that work for edu links). SEO Chatter. https://seochatter.com/how-to-get-edu-backlinks/

How to get edu backlinks to boost your search traffic. (2021, August 6). *AZ Big Media.** https://azbigmedia.com/business/how-to-get-edu-backlinks-to-boost-your-search-traffic/

Jobin, A., & Ziewitz, M. (2018, March 6). Organic search: How metaphors help cultivate the web. Alexander Von Humbolt Institut Für Internet und Gesellschaft. https://www.hiig.de/en/organic-search-metaphors-help-cultivate-web/

Killoran, J. (2013). How to use search engine optimization techniques to increase website visibility. IEEE Transactions on Professional Communication, 56(1), pp. 50-66, doi:10.1109/TPC.2012.2237255

Moogan, P. (n.d.). Link building tactics. Moz. https://moz.com/beginners-guide-to-link-building/tactics

Moogan, P. (n.d.). The beginners guide to link building. Moz. https://moz.com/beginners-guide-to-link-building

Moogan, P. (n.d.). Types of links. Moz. https://moz.com/beginners-guide-to-link-building/types-of-links

Mu, J. [@JohnMu]. (2018a, September 3). Because of the misconception that .edu links are more valuable, these sites get link-spammed quite a bit, and because of [Tweet]. Twitter. https://twitter.com/johnmu/status/1036538249488068608

Mu, J. [@JohnMu]. (2018b, 15 November). Are you suggesting they should be valued less given how many spammy links people place there? [Tweet]. Twitter. https://twitter.com/JohnMu/status/1063021883292037120

Nobel, S. (2018). Algorithms of oppression: How search engines reinforce racism. New York: NYU Press.

Portent. (2012, July 30). 7 strategies for getting .edu links. https://www.portent.com/blog/seo/strategies-for-getting-edu-links.htm

Reidsma, M. (2019). Masked by trust: Bias in library discovery. Sacramento, CA: Library Juice Press.

Sayre, F. [@somuchforsomuch]. (2019a, November 19). As a STEM Librarian I get these annoying random requests from companies (e.g. mining companies) to add a link on [Tweet]. Twitter. https://twitter.com/somuchforsomuch/status/1196860128927944704?s=20

Sayre, F. [@somuchforsomuch]. (2019b, November 19). Don't do this. I don't know exactly what they're doing but it's probably an SEO thing or they want to [Tweet]. Twitter. https://twitter.com/somuchforsomuch/status/1196860597352062976

SEO.co. (n.d.) SEO industry market size. SEO.co. https://seo.co/market-size/

Swanson, B. (2019). Website link building essentials. Flashpoint Marketing. https://flashpointmarketing.biz/link-building-essentials/

Veenstra, N. [@Letterzaken]. (2018, November 15). So you are actually saying that .edu (as well as .gov) links are equally valuable as links from other domains [Tweet]. Twitter. https://twitter.com/OptimusOnlineNL/status/1063018849170345984

Zhang, S,. & Cabage, M. (2017). Search engine optimization: Comparison of link building and social sharing. Journal of Computer Information Systems, 57(2). pp. 148-159.

Ziakis, C., Vlachopoulon, M., Krykoudis, T., & Karagkiozidon, M. (2019). Important factors for Improving Google search rank. Future Internet, 11(32).

Abstract

Despite a long-overdue push to improve the accessibility of our libraries’ online presences, much of what we offer to our patrons comes from third party vendors: discovery layers, OPACs, subscription databases, and so on. We can’t directly affect the accessibility of the content on these platforms, but rely on vendors to design and test their systems and report on their accessibility through Voluntary Product Accessibility Templates (VPATS). But VPATs are self-reported. What if we want to verify our vendors’ claims? We can’t thoroughly test the accessibility of hundreds of vendor systems, can we? In this paper, we propose a simple methodology for spot-checking VPATs. Since most websites struggle with the same accessibility issues, spot checking particular success criteria in a library vendor VPAT can tip us off to whether the VPAT as a whole can be trusted. Our methodology combines automated and manual checking, and can be done without any expensive software or complex training. What’s more, we are creating a repository to share VPAT audit results with others, so that we needn’t all audit the VPATs of all our systems.

Ethical UX

Photograph by Stefan Bauer

This is Albert Speer's German Pavilion for the 1937 World's Fair, representing Germany's fascist government. It is a monstrous, imposing, threatening tower of might. It doesn't have statuary embodying those values, but the building itself represents them.

I think we can best see the values built into Speer's building by comparing it to the German Pavilion done 21 years later, for the 1958 World's Fair, by Egon Eiermann. It is a three story, flat, horizontal building. It feels tranquil and calm. It is all glass, representing transparency and democracy. The World's Fair is a place where you represent what you believe is right in the things you make. So these were very intentional choices by the architects, to encode these values into their buildings.

Chart by Steve Nass

But this is not just buildings. Gerrymandering, for instance, is also a design that reflects the values of its creators. This graphic is an example of how the redrawing of political boundaries works.

If you have, for instance, 100 voting precincts, and 60 of them vote for a Democratic candidate, and 40 vote for the conservative candidate, split into equal districts, you will have 5 districts sending Democratic representatives to Congress. But if you redraw those districts and put as many blue voters as you can into two of those districts, you can send 3 Republican candidates to Congress even though they are outnumbered by 20%.

From Mike Monterio's slides for How to Fight Fascism

This is a design, and it represents the values of the people who created it. If you want to see what this design looks like in real life, above is North Carolina's 12th Congressional District. Doesn't it seem like a really obvious shape for a congressional district? The District has three cities in it, that tend to vote Democratic. The party that was in control, the Republicans, redrew this district to load it up with the opposition party, potentially thwarting the will of the people, with design.

From @Nadaleen

In our tools, if someone searches for "children's literature" and our discovery layer suggests that they might be interested in "children's sex literature," what values do those reflect? Access?

Do we value our users more than the appearance of convenience?

This is the Brooklyn Public Library's online library card application. You don't have to go in and fill out a paper form. But this is one of the questions they ask: gender. And they give exactly two options: Male, or Female.

If I'm a transgender woman and I encounter this question, how do I answer it? Do I answer for who I am, or do I answer what it says on my birth certificate? After all, they don't say what they will do with this information, or who will see it. If I haven't come out to my friends and family, do I dare answer this truthfully?

If libraries are supposed to be a safe place, why would we ask this question, and make someone justify themselves just to use our services?

What are our values? Equity? Privacy? Do we value our users more than our fetish for data collection?

If we search for information about stress in the workplace, and our tools tell us that stress is probably related to women in the workplace, what are our values? Equity?

If our tools will only work on the newest technology, what are our values? Access? Equity?

Ethical design is thinking about what happens in the world if we make this thing. You have to think about how the people who use your design will be affected. How do the choices we make when creating something help or hinder those who will use it? Does that sound familiar to you? That sounds like UX.

This should be our bread and butter. Because a graphic designer doesn't necessarily worry about how someone will interpret a poster (even if they should). An industrial designer doesn't necessarily have to worry about how people will react to what they've created (even if they should). But an experience designer thinks about the experience of the people who use our tools. It's in the title! We have the tools.

This is a screenshot from the marketing websites of Analytics on Demand from Gale. It's an analytics service that is provided by the company that will give you "household-level data" about your users. That means that instead of anonymous numbers in a row of spreadsheets, you can know the "age, race, and ethnicity" of the people behind those numbers. But what good is that information? Are demographics, our racial backgrounds, our genders, what cause us to make decisions, to want things, to do searches in the library? How can this information possibly help a library?

They also claim they can provide you with voting information about your patrons which, I suppose, can be valuable if you are a public library with an upcoming millage, but if scares the hell out of me. Look at that map: do you see people behind the pin points, highlighting where all of the libraries patrons are?

The way this service works is that you upload all of your own information to their friendly servers, and then they crunch your numbers and spit out some dehumanizing maps and charts for you as the last vestiges of your patrons' privacy are flushed away. This service provides them with a lot of value, too, of course. They want the data more than they want to provide you with this analytics service.

Personas begin with us trying to better understand our users. Below are some examples of personas from Montana State University Libraries. They've done a terrific job of documenting and researching their personas, and they've been useful to me as I created and refined my own.

They have an undergraduate persona, a graduate student persona, and they also have faculty, including an adjunct (whose salary is approximately half of what a barista at Starbucks makes.)

But the longer I've used personas, and the more I've talked with others who use them, I've begun to feel uneasy about them as a design tool, at least in the way they are commonly used. Do you see anything strange about the personas above?

Everyone is smiling. Even the adjunct professor is smiling! (I used to be an adjunct at GVSU, and I can tell you that I didn't have time to smile, because I had to work 2 other jobs to make rent.)

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<p>Full disclosure: below are the smiling people on the GVSU personas. We're not immune from this.</p>

<div class="center">
    <img src="https://mreidsma.github.io/ethicalux/img/gvsupersonas.jpg" alt="Student personas from Grand Valley State University Libraries" />
</div>

<p>How can we make these design tools and our research reflect the complexity of our users? Think about situations that might bring someone to a library. Because, your users might not have a choice about coming to you. They might be in crisis, afraid, numb, bored, angry, sad, or some combination of these things. Are we ready to help them when they come?</p>

<p>Deirdre Costello from EBSCO's User Research team shared <a href="https://medium.com/@indiyoung/describing-personas-af992e3fc527">Indi Young's article on crafting personas without demographics or photos</a>. Indi proposes that instead of leading with demographics, you lead with needs, and use description and narrative instead of "facts". Demographics aren't necessary for a persona to be useful, but they might trigger biases about particular groups of people in those who use them to design.</p>

The Topic Explorer is one of my favorite features of Summon, the discovery layer we use at GVSU. It is designed to give contextual information about broad searches (or what we often call crummy searches, 1-2 words at most). In the example given with Summon's marketing material, searching for "heart attack" will expand the search and bring in an encyclopedia article about myocardial infarction, which is the medical term for heart attacks. Because medial literature is going to use this terminology, the user gets more academic materials and learns the proper terminology for their field of research.

I did an analysis of the Topic Explorer last year, because I really love this feature, and I wanted to make it better. 93% of the time, the topic was at least on the same topic as the user's search. That's pretty good success for an algorithm.

But the more important question isn't about the tool's success, but what happens when it fails. What about the other 7% of the time, when it shows some off-topic entry?

We don't know how the Topic Explorer works, because the algorithm is proprietary. So we don't know what makes it decide to choose one topic over another. We don't know, for instance, what makes it choose "Sexual abstinence" if you are searching for virginity. These are not synonyms, as you can be sexually abstinent and not be a virgin. There are, in fact, strong religious and political connotations to those two terms, and conflating them in this way makes it appear that ProQuest, and for the purposes of our users, the library, are making a political stance.

But no one sat down and consciously connected sexual abstinence and virginity together at ProQuest, so how did they get matched? What happened?

From Damn You, Autosuggest

What happened in this discovery tool to connect a search for "new york city waste" to "new york city women"?

What happened to connect the idea of rape with hearsay testimony?

Everyone is a
Distance Learner

Don't believe me? Let's try an experiment.

Let's say we're going to build a library that Hannah Marburger might have gone to in the mid-1970s.

First, we'll put a sign out in front, as well as some landscaping. We want it to look nice when folks arrive so they know where they are and that we care.

We'll locate our card catalog and circulation desk right up front, but then we'll fill up most of the space with resources. Rows, and rows, and rows, and rows of resources. Since navigating those resources can be tough, we'll put some wayfinding tips right up by the card catalog. So when you find what you want, you can write it down with your little golf pencil on the back of some scrap paper we chopped up for you, and then you can look at the wayfinding to see where you need to go to find that call number.

Just in case the wayfinding doesn't help, we'll put a reference desk right back in the stacks. And then we'll put some exhibits, and some new books displays and a bulletin board with important news where everyone who walks in will see it. And finally, we'll post our hours, and some maps of the building,and some helpful tips (probably on a passive-aggressive sign) right up by the front door.

No one would build a library like this now, would they?

Here's the thing: we still build the libraries. This is how we think about our libraries, as physical spaces full of resources. Even though we might not consciously realize it, that connection between the physical library and the service is coming out in our online tools.

When we move physical items from the physical world into software, the new digital versions are often just replicas of their tangible counterparts. In design, this is called skeuomorphic design.

"But we do offer help!"" you say. Do we? I have seen the ways that we offer help to users. We overload them. We send them links to LibGuides. And the thing is: this is really good stuff! If only they would read these help documents we have written, we likely would make things better for our users.

I struggled for a long time trying to find an example of an industry that faced a similar issue: having important information that they needed to convey where the users actively ignored any attempt at communication.

I couldn't think of much, and while I was sitting on the runway on my way to the conference, I tuned out something the flight attendant was saying and really tried to get some thinking done. I wanted to know who else was trying to communicate information that was important to everyone, and that users would really want to know if something went wrong. And then I remembered, that on an Iceland Air flight last year, I was enamored by the safety video they showed me that was unlike any safety video I'd ever seen before.

The video starts off in a fairly conventional way, showing travelers on an airplane. But I don't care much at this point, because I'm already on an airplane, and being on an airplane isn't why I am on an airplane.

As I watched, I realized that they had come up with a really smart way to get me to pay attention: they connected the information they were trying to get across to my whole reason for being on the plane: I was going to Iceland. They found a way to keep me in my story, my adventure in the Icelandic landscape, and bring the information they thought I should know right there.

If you watch the video above, you'll see that they manage to incorporate not just beautiful vistas of Iceland into the backdrop: they manage to work in physically the actual safety instructions with the landscape.

When I got on the plane, I was already in Iceland in my head. Iceland Air realized to get me to pay attention, they had to understand my story, my motivation. And they met me where I was.

How do we connect people with their stories in libraries? How do we go to where the students are, online, shedding our dependence on our physical spaces?

Discovery's promise of a simple search experience works for users, more often than not. But discovery's external simplicity hides a complex system running in the background, making decisions for our users. And it is the rare user that questions these decisions. As Sherry Turkle (1997) observed, users approach complex systems like search engines at “interface value.” Since the interface is simple, they are content to assume that the underlying mechanism that makes them work is also simple. They are often unaware that complex algorithms help determine what results are shown and what results are excluded. As library search in particular has become simpler, the complex workings of our search tools have, like Google's, receded into a black box. As Tim Sherratt (2016) reminds us “it's not just the simplicity of that single search box, it's our faith that search will just work.”

Even within libraries, algorithms are not well understood. A common definition is that an algorithm is a set of instructions that take an input and produces an output. But translating this simple definition into a model that explains how a single search box can produce millions of possible results is a challenge. Describing an algorithm in these terms is another attempt to put a simple interface on a complex idea. Frankly, with algorithms, the input and output aren't the most important parts. The instructions are what matter, since they help to determine how the input is interpreted and how the output will be generated. Perhaps a better way to define algorithms is by following Christopher Steiner (2012), who compared them to “decision trees, wherein the resolution to a complex problem, requiring consideration of a large set of variables, can be broken down to a long string of binary choices” (p. 6). An algorithm, then, can be thought of as a series of if/then statements, where a number of parameters are examined and the results can affect how the input is transformed along the way. Algorithms don't have to be computer code, either. As a child I loved the Choose Your Own Adventure series, and they were in their own way a literary algorithm. Today, what stories appear on your Facebook news feed and what ads you're shown as you move about the web are all determined by algorithms.

But rather than objective methods of analysis, algorithms are systematic instructions created by humans that computers follow. Ian Bogost (2015), writing in The Atlantic, claims that algorithms are closer to caricatures then deities. Algorithms, he writes,“ take a complex system from the world and abstracted into the processes that capture some of that systems logic and discard others.” This is important to remember, however, because our view of algorithms as objective processes is dependent on the absence of human interference. But as Andreas Ekström (2015) reminds us in his TED talk, The Moral Bias Behind your Search Results, “behind every algorithm is always a person, a person with a set of personal beliefs that no code can ever completely eradicate.” We might add that behind every algorithm is also a company, with obligations to its business model and shareholders.

To the extent that we understand algorithms, they take on a more significant role than simply a set of instructions a computer uses to weight the “relevance” of possible results. As Tarlton Gillespie (2014) has noted, “more than mere tools, algorithms are also stabilizers of trust, practical and symbolic of assurances that their evaluations are fair and accurate, free from subjectivity, error, or attempted influence” (p. 179). Users' faith in search algorithms frees us from having to evaluate the inner workings and possible biases of tools that have become fixtures in our daily lives. The French philosopher Bruno Latour has said that “in so far as they consider all the black boxes well sealed, people do not, any more than scientists, live in a world of fiction, representation, symbol, approximation, convention… they are simply right” (qtd. in Dormehl, 2014, p. 236).

Providers also capitalize on this faith. Marissa Mayer, while at Google, said, “It’s very, very complicated technology, but behind a very simple interface. Our users don't need to understand how complicated the technology and the development work that happens behind us is. What they do need to understand is that they can just go to a box, type what they want, and get answers” (Vaidhyanathan 2011, p. 54). That our perception of search tools’ trustworthiness should be so uncritical has been a boon to the industry. In librarianship over the past few decades, the profession has had to grapple with the perception that computers are better at finding relevant information then people. On the technical services side of the profession, we have responded to this perception by pushing for more integration with our various search tools. Over the past decade discovery tools, which search a unified index of providers from a single certain point, have changed the way that many library users do research. As our discovery tools have become more complex, much of the discussion and critique has centered on the simplification of the search process, the effectiveness of user interface elements, and the integration with other library systems and services. I have found no substantive evaluation of the search algorithms of commercial library discovery platforms in the literature.

The task of determining how successful our library discovery tools are at presenting good results is thus stymied by user perceptions of what the tools are capable of, the opacity of the business model of our search engine providers, and the fact that underlying everything was a series of instructions written by people with a particular point of view. Yet as academic libraries providing our users with search tools, we need a way to evaluate the contents of the results. In Safiya Noble's (2012) research on commercial search engines like Google, she highlights how the results Google shows users are understood themselves to be a reflection of the truth. When students in Noble's classes search for “black girls” and Google returns porn websites (p. 38), what are African-American girls to think about their own identity? In situations like this, we can make a clear argument that the results are not only not relevant, but that they appear to be biased. But Google's results for “black girls” also highlights the moral question underneath this: if indeed algorithms are created by people with biases and perspectives, who should be accountable for these kinds of search results? (Google often defers to the algorithm, refusing to accept blame since the computer has done the selecting. They fail to mention that engineers programmed the computer to do the selecting in the first place (Dormehl, 2014, p. 226).)

In academia, we like to assume that our results do not necessarily send the same message to users as those of commercial search engines. While Google is showing you “answers,” academic discovery tools are reflecting the scholarly conversation around a subject, and so wide ranges of opinions are to be expected. (It is doubtful that our users are as confident in this distinction as library folk are.) With the number of results that are returned from our commercial discovery services (easily over a hundred thousand on many of the most common searches) along with the trouble in ascertaining the meaning of “relevance,” it can be a challenge to make a solid case for what constitutes a “good” algorithm. But just because this kind of analysis is challenging, or that doing it might call into question our own faith in the objectivity of our discovery service's algorithms, doesn't mean we should abandon it. As the law professor Danielle Citron has argued, “we trust algorithms because we think of them as objective, whereas the reality is that humans craft those algorithms and can embed in them all sorts of biases and perspectives” (as cited in Dormehl, 2014, p. 150). We need to evaluate these algorithms for accuracy and bias.

From following the discussions at professional conferences, on list-servs, and in the professional literature over the past few years, I've seen a sort of acceptance from librarians of the black box nature of our discovery search algorithms. Like our users, by not questioning how the black box works, we can continue to keep have full trust and it's effectiveness. Of course, it is also difficult to test the “effectiveness” of many of our search tools, since the results are often sorted by “Relevance”. The problem with evaluating relevance, is that once you start to measure the relevance of a result you bump up against an important question that is not part of the library discovery service: relevance to whom?

Introducing the concept of relevance automatically brings the supposed objectivity of algorithms into question. In Tarleton Gillespie's (2014) analysis of the “political valence” of algorithms, he cites six dimensions of algorithms that we can examine that have political or moral dimensions. The third and fourth dimensions are “the evaluation of relevance” and “the promise of objectivity” (p.168). As Introna and Nissenbaum (2000) have noted in their work on the politics of search engines, “experts must struggle with the challenge of approximating a complex human value (relevancy) with a computer algorithm” (p.174). Gillespie's (2014) analysis is less optimistic about the engineering attempts at relevancy: “'relevant' is a fluid and loaded judgment … engineers must decide what looks 'right' and tweak their algorithm to attain that result… or make changes based on evidence from their users, treating quick clicks and no follow-up searches as an approximation, not of relevance exactly, but of satisfaction” (p.175).

At Grand Valley State University, we have used the Summon Discovery service from ProQuest since 2009. In 2013, Summon rolled out its new “2.0” product, with a number of features that were meant to move it beyond just the traditional rows and rows of relevance-ranked results. One of those new features was similar to new work coming out of Google around the same time. In Summon 2.0, the right hand sidebar was reserved on new searches for something called the “Topic Explorer.” Topic Explorer was designed to “dynamically display background information for more than 50,000 topics” (ProQuest, 2013) by showing reference articles for the topic the user was searching for. The reference articles would “provide users with valuable contextual information to improve research outcomes” (Ibid). ProQuest did this by “analyzing global Summon usage data and leveraging commercial and open access reference content, as well as librarian expertise” to establish “large-scale, data-driven contextual guidance” (Ibid).

Behind the corporate lingo, the goal of Topic Explorer was to show reference material for broad searches by drawing on entries from Wikipedia, Credo Reference, Gale Virtual Reference Library, and more. At GVSU, we’ve had Wikipedia and Gale Virtual Reference Library enabled since we went live in early 2014.

The Topic Explorer also benefitted from another Summon 2.0 feature: query expansion. Since users don't always know the best keywords or controlled vocabulary words for their particular academic search, Summon 2.0 would automatically match many common keywords with additional terms that would return results from more technical literature that were relevant for the users search. The example given in the press release is a search for “heart attack.” Summon 2.0 will also return results that match for “myocardial infarction,” the technical term for a heart attack (ProQuest, 2013). Doing a search on GVSU's instance of Summon for “heart attack” also returns the Wikipedia article for “Myocardial Infarction” (Figure 1).

Figure 1

While the exact algorithm that chooses the terms remains a bit of a mystery, Brent Cook (2016), the current Project Manager for Summon, explained a bit behind how the tool works in an email to the Summon Clients list-serv in January 2016:

”We use our log files to identify topics and synonyms for these topics. We index these topic names and synonyms using Solr. We then match the Wikipedia and encyclopedia articles to topics. In the case of Credo, we match through their topic taxonomy, which has links to their encyclopedia articles. Because of this, you will see differences between searches done on the individual platforms as compared to the Topic Explorer in Summon.“

When I first began sketching out tests to measure the effectiveness of algorithms, I was drawn to the one behind the Topic Explorer because it was professing to do something different from all other discovery search results sets. By returning only a single result and placing the result on the right side on wider screens (mirroring Google's Knowledge Graph), the Topic Explorer is meant to say, "this is what you are searching for.” Because there is only a single result, there is a confidence inherent in the design that would make this a test subject for algorithm effectiveness.

What's more, as I was in the planning stages for a project to examine the Topic Explorer, a colleague reminded me of a common search he uses to examine new search tools, “stress in the workplace.” Run in our instance of Summon, the Topic Explorer returned the Wikipedia article for “Women in the workforce (Figure 2). This seemed to be something else worth examining, since rather than just accuracy, this particular result contained what appeared to be gender bias. The result was equating stress at work with working women. I tweeted about the search (Reidsma, 2015), and ProQuest made a change in the algorithm to fix that particular search (ProQuest, 2015). However, I quickly discovered that they had merely blocked the keywords "stress in the workplace” from returning a topic. A search for “stress in the workforce” still returns “women in the workforce,” more than three months after they made their change.

Figure 2

I became interested in testing not just for accuracy in the Topic Explorer, but also for situations where inaccuracy crosses the line into bias. The study of bias in search engine results has a fairly long history. In 2002, Mowshowitz and Kawaguchi emphasized the need for this kind of analysis, since “the role played by retrieval systems as gateways to information coupled with the absence of mechanisms to insure fairness makes bias in such systems an important social issue” (p.143). Indeed, many such studies have looked for anomalies in results. According to Eslami et al. (2015), “researchers have paid particular attention to algorithms when outputs are unexpected or when the risk exists that the algorithm might promote antisocial political, economic, geographic, racial, or other discrimination” (p.154) Indeed, examining problematic results in the Topic Explorer felt like not just a first step in building a toolkit for examining library discovery algorithms, but also of highlighting the moral responsibility we who create technologies for libraries are beholden to. The Topic Explorer itself is designed to change a users’ behavior, to offer “ contextual information to improve research outcomes” (ProQuest, 2013). As Luke Dormehl (2014) reminds us, because technology aims not to describe but to change the world, it is “a discipline that is inextricably tied in with a sense of morality regardless of how much certain individuals might try to deny it” (p.132).

Once I understood the scope of my project, I knew I needed a way to examine a large sample of searches that included Topic Explorer entries. Since not all searches have a Topic Explorer, I couldn't just wade through the ProQuest search logs. Rather, I decided to specifically capture the searches that returned Topic Explorer results. I wanted to know what the search terms were, what topic explorer entry came up, what the entry said, and which provider it was from. Following on Cook’s comment that the Summon Topic Explorer algorithm will return different results in the native tools, I wanted to also examine what results I would have gotten from Wikipedia or Gale Virtual Reference Library if I had searched there directly using the same search terms.

First, I added a small jQuery function to our custom JavaScript file that runs in Summon. The JavaScript looks for Topic Explorer entries on search result pages, and then sends the search terms, the entry title, source, and text to a simple PHP file that saves the data into a MySQL database. I then created a web page that returned and sorted the results. The tool first groups all of the search queries together, counting the number of times the exact same keywords have been used, and then displays the results in chronological order.

I then waited a few months to collect data, and reviewed the first 8,000 search queries that produced a Topic Explorer entry. In most cases, the Topic Explorer showed an entry that matched exactly or very closely the text entered by the user (or, at least the same words, if not in the same order). In one grouping of the page, you'll see a search for “transactional analysis” return a Wikipedia article of the same name, a search for “french revolutionary wars” return the Wikipedia article “French Revolutionary Wars,” and a search for “chinese herbal medicine” return the Wikipedia entry for “Chinese Herbology.” These examples are numerous, and show the benefits of the Topic Explorer algorithm at matching these general searches with relevant reference material.

The algorithm also proved to be quite good at picking up related terms in some cases, regardless of what keywords were entered. At times, this was because of the query expansion, as in the “heart attack” search example. Other times, however, the Topic Explorer algorithm was able to find related entries that were relevant without relying on query expansion. For instance, a search for “ends justify the means” returned the Gale Virtual Reference Library entry for “Consequentialism,” a philosophical outlook in which outcomes are enough to justify actions. Searching the Gale Virtual Reference Library for “ends justify the means” returns over 2,800 results. The first hit is the “New Testament,” and nowhere on the first page of results is “Consequentialism.” Here is a case where Summon's custom indexing has brought a potentially useful reference article out into a user's search.

However, often searches for specific topics were given an overly-generalized reference article, such as a search for “fetal tissue research” which returned the Wikipedia article on “Fetus.” The topic of “fetus” isn't going to be particularly relevant to a search on fetal tissue, especially since the Wikipedia article focuses on fetal development during pregnancy. Searching Wikipedia for “fetal tissue research” returned over 800 results, none of which matched the search directly, either. The majority of the results on the first page were political entries, covering politician or political party positions on fetal tissue research. The ninth result was "Fetus.” In these situations, it seemed that Summon wasn't improving on the native search, but it wasn't hurting things, either.

However, there appeared another group of searches that returned Topic Explorer entries that didn’t match the search terms at all. Of the 8,000 search queries I examined, I flagged 561 as being inaccurate, usually for matching an incorrect Topic Explorer entry with the search. Many of these errors fell into predictable categories, although not all. There were topical searches that returned known item entries, like the search for “skin to skin contact” that returned the Wikipedia page for an Australian pop song called “Skin to Skin.” Often these were subject searches that returned a particular journal, such as the search for “marriage and family” that returns the Wikipedia article on the “Journal of Marriage and Family.” These are at least understandable, if we assume that the algorithm is weighing the keywords in the entry's title more heavily than other factors. More puzzling is the search for “poems” (granted, a terrible search) that returns the Gale Virtual Reference Library's article on Ralph Waldo Emerson. While Emerson was a poet, it hardly seems helpful to introduce the curious user to the entire breadth and history of poetry by offering up a biography of one American writer.

Another group of problems concerned searches for known items. Of these, many returned the wrong known item, usually due to a pattern of words in the titles that was similar. Some examples of this were the searches for “return of the king,” where users expected information on the Tolkien novel but instead were shown the Wikipedia entry for a documentary called “The King of Kong: A Fistful of Quarters.” Searches for the “city of god” (which could either be a topical or known item search) were shown the page about a non-fiction book called “Farm City: The Education of an Urban Farmer.” Many of these known item searches that returned the wrong item concerned journals. Searching for “american journal of transplantation” will get you the “American Journal of Sociology,” and the “journal of aquatic sciences” will offer up the “British Journal of Psychiatry.” No matter how you search, looking for “the prince” or “the prince machiavelli” will get your research on “Prince, 1958-” the “exciting live performer and prolific singer-songwriter,” courtesy of Gale Virtual Reference Library.

Sometimes a topical search returns topical information, but on the wrong topic. While some combinations seem downright nonsensical (“women are homemakers” returns “sociology”), some can be inadvertently humorous, depending on your political or moral leanings. For instance, searching for “united states healthcare system” returns the Wikipedia article on “United States patent law”, which may or may not be a comment on the hold that Big Pharma has on our current healthcare. A search for “princess diana” returns the Gale Virtual Reference Library article on “Wonder Woman.” The search for “creation of patriarchy” perhaps rightly introduces the reader to Michelangelo’s “Creation of Adam” painting, for if there were to be a starting point of the patriarchy, why not at the beginning? A sad commentary on the rising cost of college tuition might be the search for “united states egg price” which gives us Wikipedia's entry on “Student financial aid in the United States.” Those concerned with the influence of sports in our culture will no doubt be pleased to see a search for the “culture of sports” return “the culture of narcissism,” and it does seem appropriate to learn more about “legal drugs in the united states” by studying “Public holidays in the United States.” Perhaps my favorite, “branding” returns “BDSM,” the Wikipedia article for Bondage, Discipline, Sadism, Masocicism dealing with fantasy role play. It's hard not to read that as a statement about corporate image creation.

While the sample of incorrect Topic Explorer associations I shared above might be read as sly commentary on our political or educational systems, other results in the Topic Explorer presented a darker perspective. This is not uncommon when dealing with algorithms. Mike Ananny (2011), writing in The Atlantic, told of installing Grindr, a location-based dating and socializing app for gay men, and looking at the algorithmically generated “related” apps. Included was a “Sex Offender Search” app. In teasing out how the algorithm decided that gay men and sex offenders were topically related, he notes that “reckless associations—made by humans or computers—can do very real harm especially when they appear in supposedly neutral environments.”

In 2013, Harvard professor Latanya Sweeney published an article that argued that searching for “racially associated” names on Google and other services had a significant effect on whether an advertisement implying that the person you were searching for had been arrested. “Black-identifying names” like DeShawn and Trevon were 25% more likely to be shown an ad suggesting that the person had been arrested than names associated with whites, like Jill or Emma. These results are not connected to whether the names actually have an arrest record, but seem to be algorithmically biased.

Of the 561 Summon queries I judged as returning incorrect Topic Explorer results, I flagged 54 as displaying potential for bias (including the BDSM entry I just mentioned). That is 9.63% of the problematic search queries, or .68% of the 8,000 I reviewed.

Mowshowitz and Kawaguchi proposed two kinds of bias that can come from matching algorithms. The first is “indexical bias,” where bias is evident in the selection of items. “Content bias,” however, comes from the content of what was selected (2012, p.143). Of the 54 potentially biased results, the majority were instances of “indexical” bias, where the matched subject term was enough to imply bias in the matching algorithm.

Indexical bias most often occurred where a search query was matched with an article that implied a social, moral, or political comment on the original search terms. For instance, a search for “corrupt government in united states” returned the Wikipedia entry for “Government procurement in the United States,” making the implication that the Government's supply chain is inherently corrupt. Another example was a search for “pollution levels in the usa” which offered the user the Gale Virtual Reference Library article on “Education in the United States.” Say what you will, we've had vigorous debates about education in America, but I don't think it's quite reached the point where we can classify it as smog.

Bias cut the other way, at times, such as a search for “history of human trafficking” that returned Wikipedia's entry for the “History of human sexuality,” an entry that may be related to trafficking but by no means subsumes the entire topic.

This isn't to say that bias was put into the algorithm intentionally. However, the end result is the same, regardless of intent. The important thing is to understand how the results were mapped to specific search terms and address the problem.

The majority of the 54 biased search results were related to women, the LGBT community, race, Islam, and mental illness. I’ve reproduced each of these categories below, including any spelling errors present in the original search queries.

Biased Results About Women

By far, the most problems encountered were related to gender. Here we see the comparison that started my examination of the Topic Explorer, the result that says “women” are the same as “stress” when found in the workplace. Perhaps one of the most offensive entries suggests that researchers looking into “rape in united states” have a look over the Wikipedia article on “Hearsay in United States law,” which describes unverified statements made about an event while not under oath (Figure 3). Implying that a search for information on rape in this country is tantamount to searching for unverifiable claims goes beyond merely being incorrect, it's offensive. A search through the text of the Wikipedia entry on Hearsay shows that the word “rape” never appears in the text.

Figure 3

Another topic is a bit perplexing since they seem to reflect one side of contemporary moral debates: a search for “virginity” that produces the entry for “Sexual abstinence” implies a certain moral or political stance, these days. Especially since Wikipedia has a perfectly useful entry on Virginity. (The word virginity only appears on the Sexual abstinence page three times, and two of those are in see also references. In contrast, it appears 121 times in the Virginity entry, including in the title.) Of course, the Summon results page indicates that they have expanded the default search of virginity to include “sexual abstinence.” Removing that query expansion will return the Wikipedia “Virginity” entry. While query expansion works well in the case of using synonyms, this query expansion is a different matter. One can be sexually abstinent without being a virgin, and so including the query expansion makes the Topic Explorer entry look like a synonym for virginity.

At least a biased result you'd get when searching for “the birth of feminism” has some technical explanation: when you're shown “The Birth of Tragedy,” hopefully you'll understand that the algorithm was matching a pattern of words, not comparing feminism with tragedy. Likewise, the “corruption in the army” search that returns the entry on “Women in the military” is matching a pattern in the title and using a synonym: you can try this experiment yourself by putting whatever you like in place of the “x” when visiting GVSU's Summon: “X in the military” will almost always return the Wikipedia entry for “Women in the military,” as if the Topic Explorer has become a sort of Mad-Libs. The same pattern is at work with many searches for "women in the,” as evidenced by the suggestion that the only role for women in the government is in the military. Matching “history of women's rights” with French far-right movements it latching on to the indexical term “right,” although missing the different context and meaning, and implying that women’s rights are a form of extremism. The word “women” never appears in the entry on French's far-right movements, indicating that the algorithm is overemphasizing the keyword matching in the title.

Another pattern matching error that appears biased is the suggestion that like “indulgences in the middle ages,” women during that time were tools to be handed out by the church to reduce the time someone spent in purgatory. As for the “stress in the workplace” search that ProQuest fixed, you can still find the biased result by switching to workforce. Nearly any noun can be added to a search “X in the workforce” and you'll still get the entry about women.

Biased Results About the LGBT Community

Here we have domestic violence equated with domestic partnership (Figure 4). While both of these subjects apply to both hetero- and homosexual relationships, domestic partnership began as a way to recognize same-sex unions. With the amount of controversy surrounding sax-sex marriage in the United States, this kind of “reckless associations” can add fuel to an already contentious debate.

Figure 4

Another match implied either that the only literature available for or about lesbians is fiction. When searching for “lesbian literature,” the Topic Explorer shows an entry for “lesbian fiction,” as well as the “Related topics” of “science fiction” and “speculative fiction.” This likely stems from a decontextualized association between the term literature and the term fiction. However, a search for “gay literature” in Summon returns the Wikipedia article “Gay Literature,” and Wikipedia has an entry entitled “Lesbian literature.” Even more perplexing is the fact that the Wikipedia entry for “Lesbian fiction” was redirected to the more broad entry “lesbian literature” in October 2015. I am writing this four months later, and the Wikipedia entry in Summon’s index still has not been updated.

The final match in this category equates “crimes in the community” with “Healthcare and the LGBT community.” Implying that providing healthcare to a particular population is a crime, especially a community that already suffers from overt prejudice and discrimination, is not a stance that libraries want to be associated with.

One other topic was initially flagged, although on investigation I decided to remove it from the examination. Searching for “lgbt youth” in Summon will return the Wikipedia entry on “Suicide among LGBT youth.” There is no Wikipedia entry for “lgbt youth,” and in fact a search on Wikipedia for that topic returns the entry for “Homelessness among LGBT youth in the United States” and “Suicide among LGBT youth” as the first two results. This is an instance where the algorithm seems to be zeroing in on an entry that includes the search keywords frequently, because sadly, much of the discussion around LGBT youth today centers around suicide and homelessness.

Biased Results About Islam

In searches about Islam that returned a Topic Explorer result, Summon did consistently well. This is largely due to a number of topic-specific Wikipedia articles on different aspects of Islam, ranging from articles on Islam’s historical roots, its importance to the intellectual development of Medieval Europe, as well as the religion’s more contemporary roles in the West and relationship with extremist groups.

However, some searches were clearly problematic, especially searching for “muslim terrorist in the united states,” which returned a Wikipedia article on the religion itself. Matching a search for information about terrorists with the entire religion only adds to the stereotypes perpetuated in the aftermath of terrorist attacks in Paris and California. This is especially problematic given that Wikipedia itself has an entire entry on Islamic Terrorism (there is also a Christian Terrorism entry). Why not bring up the page specifically about terrorism related to that particular religion? The word “terrorist” only appears once in the Islam article, while it appears almost a hundred times in the Islamic Terrorism article. Even “united states” appears 24 times in the Islamic Terrorism entry, while only appearing 5 times in the article on Islam the religion.

What’s more, returning a list of individuals for a search on the “islamic day of judgment” is perplexing. No where in the article does the word “judgment” appear, and except for its appearance after “modern” in the title, the word “day” is absent as well. If someone was concerned with the Islamic “day of judgment,” what would they do about a list of individuals who are identified as muslims?

Searches for “muslim schools in the us” or “islamic schools in the us” return the general entry for “Education in the United States,” perhaps suggesting to some that all schools in the United States are muslim. But this is again an example of naive pattern matching, it seems. Like the earlier Mad Libs searches, you can enter nearly any noun you like into the pattern “X schools in the US” and get this result. This would seem to be more evidence for the additional weight of the title of the topic entry.

Biased Results About Race

If you search in Summon for “white slavery,” the Topic Explorer will present you with a Wikipedia entry for “Moral Panic.” (Figure 5) Searching for “black slavery,” meanwhile, returns a blank topic explorer pane, perhaps because Wikipedia itself will offer you nearly 10,000 possible entries related to black slavery. But why is white slavery related to moral panic, while black slavery is not? It’s true that the Moral Panic article uses the phrase twice (although one of those is in the references), but Wikipedia itself also has a perfectly suitable entry on “White Slavery.” How could the algorithm make this kind of a judgment about a topic?

Figure 5

Most of the results so far have concerned indexical bias, but there are times when Topic Explorer results show both indexical as well as content bias. Searching for “the black woman,” a user will be presented with a Wikipedia entry for The Woman in Black, a horror film from the early 1980s. Strangely, Summon’s autocomplete algorithm seems to recognize that this search is probably a known-item search for The Black Woman: An Anthology, but the algorithm for autocomplete must not share what it has learned with the Topic Explorer. The content of the Wikipedia article describing the film, however, suggests that what you are looking for is a “menacing spectre that haunts a small English town.” Of course, what is throwing off the search is the addition of the definite article (common in known item searches). A search in Summon for “black woman” brings up the Wikipedia entry on “Black people,” which is redirected from the “Black woman” entry.

Making associations between business practices or child rearing techniques and Apartheid, the institutionalized segregation in South Africa that lasted until the mid-1990s is morally problematic. Likely this is because the algorithm again latches on to a pattern of words, including “in south africa” and uses the apartheid article as a go-to result. In fact, nearly any noun you add to the phrase “X in south africa” will return this result. From “freedom” to “snow” to “soccer,” nearly any search seems to imply to the algorithm, “you must be interested in apartheid.”

Further associations are to equate forced marriage in the US with the desegregation of busing during the Civil Rights movement. Since “marriage” doesn’t appear anywhere in the busing article, I’m unsure of what to make of this connection. The title of the article used in Summon was actually redirected to the “Desegregation busing” entry in January of 2013, which was before Summon 2.0 launched to the public, which presents another question: how often are these entries updated?

Many searches that involve crime or race on their own will show Wikipedia’s entry on “Race and crime in the United States.” I’ve shown the selection of four such searches from the 8,000 entries I examined. In the case of a search for a definition of “crime,” I’m especially perplexed as to why the Topic Explorer would choose the Race and Crime entry, since Wikipedia’s entry “Crime” contains the word “definition” 14 times (although some of those are in use of conceding that it is hard to agree on a consistent definition). But why bring race into question if the user only asked about crime? And why also bring crime into the conversation if the user is asking about race alone? The Wikipedia entry on Race (human categorization) contains a total of six uses of the word crime, although four of them are in “See also” notes. (Race (biology) has no mentions of crime.) This seems to be a case where the algorithm is suggesting possible cross-disciplinary connections, but it does so in a way that amplifies stereotypes. The same can be said of suggesting that poverty is a result of slavery, which is heavily tied up with race. Are we to assume that poor people are still slaves, or that only those whose lineage included being enslaved are poor? The connection is not helpful from a research standpoint, and so we are left trying to make moral or political associations between the topics.

What’s more, searching for items of importance to Africa, the continent, tend to default to topics about African-americans. For instance, “african history” and “african culture” both return articles about African-American history and culture. This isn’t dependent on GVSU being an American university, either. The result also appears at the University of Huddersfield in the UK as well as the National University of Singapore, both of which use Wikipedia as a Topic Explorer source¹. This effectively implies that Africa itself doesn’t have a history or culture of its own. Wikipedia has a perfectly serviceable article on “History of Africa” and “Culture of Africa”, each of which can be found by searching Wikipedia natively with the same keywords as the Summon search.

Biased Results About Mental Illness

Figure 6

Nearly every search I’ve conducted in Summon that includes the words “of Mental Illness” shows me the Wikipedia entry for a controversial book by the psychiatrist Thomas Szasz entitled The Myth of Mental Illness. Szasz’s argument was one with the way that psychiatry and psychoanalysis were being conducted in the mid-twentieth century, but the title of his book was not intended to suggest that mental illness does not exist. Yet Summon consistently returns this strongly suggestive result whenever users search for topics related to mental illness. Wikipedia itself has a very long and in-depth entry on Mental Disorder, redirected from Mental Illness, which even includes a sentence about the role Szasz played in the development of the legal and psychological understanding of mental illness in the twentieth-century. Yet none of this is presented to our Summon users. Rather, any search for mental illness (or, in some cases, just “illness”) gives a headline that suggests that the topic they are studying is nothing more than a myth.

Next steps

Since the goal of the Topic Explorer is to identify the underlying topic behind a user's search, incorrect or biases results can have a great impact on a user's perception of a topic. By showing results that exploit stereotypes or bias, the Topic Explorer is saying to the user, “this is what you are looking for.” The purpose of my examination was to bring these anomalies to light and start a discussion within the library community about how to improve our search tools for everyone.

Figure 7

After examining the data, I took several steps to improve Summon’s Topic Explorer for my users. First, I made some modifications to the user interface of the Topic Explorer to give users the ability to report incorrect or biased Topic Explorer results, as well as offering some contextual information on how the Topic Explorer result was chosen (Figure 7). Second, I shared the analyzed data with ProQuest’s Summon team, so that they had data on search queries done by users and the Topic Explorer results that were returned. These two steps were meant to address the results that were either incorrect or biased. By sharing the analyzed data with ProQuest, I hoped that the algorithm could be improved so that biased results would be less common. And by offering contextual information about the Topic Explorer as well as a button to report a problem, I hoped to not only encourage reports but also to remind our users that these tools are not oracles, and the truths they claim can and should be questioned.

The third change I have proposed was more of a byproduct of the analysis. When Summon first launched, we left the default Topic Explorer sources in place: Wikipedia and Gale Virtual Reference Library. When the Topic Explorer was first launched, much of the discussion on the Summon list-serv was about the “reliability” of the reference sources. Wikipedia was scorned as a useful source, and some academic libraries still only provide Topic Explorer results from subscription reference sources like Credo and Gale Virtual Reference Library.

While analyzing the data, I discovered something that I wouldn’t have suspected before wading into the details of how the Topic Explorer works. Because the Topic Explorer attempts to give a quick and dirty summary of a topic rather than a lengthy treatise. Since Wikipedia has a style guide that requires authors to start their entries with a short summary, Wikipedia entries are perfectly suitable to being broken up and shown in bits and pieces. Gale Virtual Reference Library, however, was a more typical encyclopedic style that assumed the reader would take in the entire article at once. When Summon pulled out the lead paragraph of a Gale Virtual Reference article, then, it often seemed out of place with the search terms and the Topic Explorer heading.

For instance, a search for “curiosity in children” in Summon returns the Gale Virtual Reference Library entry on “Parenting styles,” which begins:

The study of human development is centrally concerned with understanding the processes that lead adults to function adequately within their cultures. These skills include an understanding of and adherence to the moral standards, conventional rules, and customs of the society. They also include maintaining close relationships with others, developing the skills to work productively, and becoming self-reliant and able to function independently. All of these may be important to successfully rear the next generation.

This paragraph hardly gives a summary of either children’s curiosity or parenting styles! Searching for the “freedom of religion act”returned a Gale article on “Freedom of Religion,” which begins, “The most authoritative statement of Catholic teaching on religious freedom is the Declaratio de Libertate Religiosa of VATICAN COUNCIL II” before wandering off in a description of Vatican II’s role in changing the face of the Catholic Church in the twentieth century². I’m not sure that helps a novice researcher looking for information on the US Government’s 1993 Religious Freedom Restoration Act, which, incidentally, Wikipedia has a terrific entry on.

In addition, because GVSU doesn’t subscribe directly to Gale Virtual Reference Library, we found that our access to the materials didn’t always give our users the most up-to-date information. We get most of our GVRL content from the Michigan eLibrary, which purchased content in 2005 but hasn’t updated the content since. As a result, the entry shown for a search on Osama bin Laden details his life up until 2005, but includes nothing of the later developments in the War on Terror or in his assassination in 2011.

I've presented my findings to our electronic resources and collection development librarians, and hope they will agree to switch from Gale Virtual Reference Library to Credo Reference as our second source, since it lends itself to breaking out summary articles and we have a current subscription, allowing us access to up-to-date content.

The Topic Explorer was a good first step in analyzing discovery algorithms, since it's message was different than the rest of our search results. Moving forward, I hope that ProQuest will take steps to improve the algorithm that matches search results to Topic Explorer entries, while I continue to examine these “black box” algorithms for accuracy and, most importantly, bias.

Thank you to Annette Bailey, Hazel McClure, Kyle Felker, and Patrick Roth for conversations and suggestions while I worked on this project. Thanks also to Brent Cook of ProQuest for taking he research seriously, and bringing the results to the development team.

Notes

1. Of course, it’s possible that Summon is checking my IP address when doing a search and localizing. This would be common with a Google search, but I wouldn’t think it would be a good feature for a library discovery platform, since students and researchers may be living or traveling abroad, and their current location does not change the nature of the research needs. ↩
2. It also seems that Summon’s tool for scraping the content from Gale ignores font italics or all caps, so the actual entry shown in the Topic Explorer reads: “The most authoritative statement of Catholic teaching on religious freedom is the of .” ↩

References

Ananny, M. (2001). The curious connection between apps for gay men and sex offenders. The Atlantic, April 14. Retrieved from http://www.theatlantic.com/technology/archive/2011/04/the-curious-connection-between-apps-for-gay-men-and-sex-offenders/237340/

Bogost, I. (2015). The cathedral of computation. The Atlantic. Retrieved from http://www.theatlantic.com/technology/archive/2015/01/the-cathedral-of-computation/384300/

Cook, B. (2016, January 11). [summonclients] RE: Topic Explorer algorithm. [Electronic mailing list message]. Retrieved from http://mail.lists.summon.serialssolutions.com/sympa/arc/summonclients/2016-01/msg00014.html

Dormehl, L. (2014). The formula : how algorithms solve all our problems—and create more. New York: Penguin.

Ekström, A. (2015, January). Andreas Ekström: The moral bias behind your search results. [Video file]. Retrieved from https://www.ted.com/talks/andreas_ekstrom_the_moral_bias_behind_your_search_results

Eslami, M., Rickman, A., Vaccaro, K., Aleyasen, A., Vuong, A., Karahalios, K., Hamilton, K., & Sandvig, C.. (2015). “I always assumed that I wasn’t really that close to [her]”: Reasoning about Invisible Algorithms in News Feeds. 33rd Annual ACM Conference on Human Factors in Computing Systems. pp. 153-162. Retrieved from http://www-personal.umich.edu/~csandvig/research/Eslami_Algorithms_CHI15.pdf

Gillespie, T. (2012). Can an algorithm be wrong? Limn, 1(2). Retrieved from http://limn.it/can-an-algorithm-be-wrong/

Gillespie, T. (2014). The Relevance of Algorithms. In T. Gillespie, P. Boczkowski & K. Foot (Eds.), Media Technologies: Essays on Communication, Materiality, and Society.(pp. 167-194). Cambridge, MA: MIT Press.

Introna, L., and Nissenbaum, H. (2000). Shaping the Web: Why the politics of search engines matters. The Information Society, 16(3). pp. 169-185. Retrieved from http://www.nyu.edu/projects/nissenbaum/papers/ShapingTheWeb.pdf

Latour, B. (1987). Science in action: how to follow scientists and engineers through society. Cambridge, MA: Harvard University Press.

Mowshowitz, A., & Kawaguchi, A. (2002). Assessing bias in search engines. Information Processing and Management, 38(1). pp. 141-156.

Noble, S. (2012). Missed connections: What search engines say about women. Bitch, 1(54). pp. 36-41. Retrieved from https://safiyaunoble.files.wordpress.com/2012/03/54_search_engines.pdf

ProQuest. (2013). Serials Solutions Advances Library Discovery with Summon 2.0. Retrieved from http://www.proquest.com/about/news/2013/Serials-Solutions-Advances-Library-Discovery-with-Summon-2-0.html

ProQuest. (2015, November 11). @mreidsma We are working to address the issue with the Wikipedia articles.. [Tweet]. Retrieved from https://twitter.com/ProQuest/status/664561101904965633

Reidsma, M. (2015, November 11). Then I looked in Summon at a common search, and saw the sidebar: http://gvsu.summon.serialssolutions.com/#!/search?ho=t&l=en&q=stress%20in%20the%20workplace … @safiyanobel 3/3. [Tweet]. Retrieved from https://twitter.com/mreidsma/status/664508446054699008

Sherratt, T. (2016). Seams and edges: Dreams of aggregation, access & discovery in a broken world. Retrieved from http://discontents.com.au/seams-and-edges-dreams-of-aggregation-access-discovery-in-a-broken-world/

Steiner, C. (2012). Automate this: How algorithms came to rule our world. New York: Portfolio/Penguin.

Terkle, S. (1997). Life on the screen: Identity in the age of the Internet. New York: Simon & Schuster.

Vaidhyanathan, S. (2011). The googlization of everything (and why we should worry). Berkeley: University of California Press.

Edited 1/24/2017 to remove links to web page showing all results, as this tool was removed from the GVSU Libraries server. Analyzed results are still available at http://dx.doi.org/10.5281/zenodo.47723.

This week I collected all the entries and code snippets I could find for a colleague, and thought I'd post them here in case they are useful for others. If you use Sierra and the WebPAC Pro, check out these resources, since they might be useful for you.

• Creating a “placebo login” for requests from our ASRS: https://matthew.reidsrow.com/worknotes/164
• Adding modal windows to help users understand journal and microfilm/fiche requesting: https://matthew.reidsrow.com/worknotes/159
• Redesigning the login screen with two different logins: https://matthew.reidsrow.com/worknotes/157
• Show and sort all available copies of an item on a single page, rather than the silly see more page: https://matthew.reidsrow.com/worknotes/156
• Most recent redesign (includes holdings statement design): https://matthew.reidsrow.com/worknotes/151
• Redesigning the 856 field: [https://matthew.reidsrow.com/worknotes/142(https://matthew.reidsrow.com/worknotes/142)]
• Moving the MARC button and hiding call numbers on eBooks: https://matthew.reidsrow.com/worknotes/141
• Improving failed renewal request messaging: https://matthew.reidsrow.com/worknotes/135
• Creating searches that automatically add keywords for scope: https://matthew.reidsrow.com/worknotes/118
• Switching buttons to sprites, CSS styles: https://matthew.reidsrow.com/worknotes/94
• Improving infrastructure, performance updates: https://matthew.reidsrow.com/worknotes/93
• Redesigning the My Account screen: https://matthew.reidsrow.com/worknotes/85
• Redesigning the Advanced Search screen: https://matthew.reidsrow.com/worknotes/83
• How not to push test code live: https://matthew.reidsrow.com/worknotes/79
• Redesigning the no results non-keyword search screen: https://matthew.reidsrow.com/worknotes/71 and https://matthew.reidsrow.com/worknotes/74
• Switching Nearby on Shelf from an image to a text link: https://matthew.reidsrow.com/worknotes/73
• Fixing the 8 million font-size rules: https://matthew.reidsrow.com/worknotes/68
• Labeling improvements based on usability tests: https://matthew.reidsrow.com/worknotes/66
• Make sure users really want a requested journal: https://matthew.reidsrow.com/worknotes/65
• Getting feedback on what to include in a catalog using a bookmarklet (aka Make Your Own Catalog Mockup): https://matthew.reidsrow.com/worknotes/54 and https://matthew.reidsrow.com/worknotes/55
• Simplifying the two request buttons when you have an ASRS: https://matthew.reidsrow.com/worknotes/56
• Adding an alert based on holding information (eg ASRS is down): https://matthew.reidsrow.com/worknotes/53
• Redesigning the awful, awful error messages: https://matthew.reidsrow.com/worknotes/48 and https://matthew.reidsrow.com/worknotes/51
• Comparing the OPAC to the Discovery layer: https://matthew.reidsrow.com/worknotes/50
• Scraping records to get availability data: https://matthew.reidsrow.com/worknotes/40

Code Snippets:

• Reformatting the availability table in search results: https://gist.github.com/mreidsma/f6a70b55697639ba80bc
• Fixing unhelpful renewal messages in Sierra: https://gist.github.com/mreidsma/94e7e86a3b3d98fa8062
• Check a query for search term, if not there add it before submitting: https://gist.github.com/mreidsma/b7dbab00b5b3f6119a5c
• Clean up no results pages for non-keyword searches in Summon: https://gist.github.com/mreidsma/9258543
• Add modal window asking users if they want journal or article when they request a whole journal: https://gist.github.com/mreidsma/8849877 (superseded by live code)
• Add alert if an item is in the ASRS: https://gist.github.com/mreidsma/7198563
• Fix hard-coded error messages: https://gist.github.com/mreidsma/6872739
• Change placeholder text for author searches: https://mreidsma.github.io/2015-MLA-Tech-Trends/#/40

Live code for GVSU:

• https://github.com/gvsulib/opac/tree/debug (Yes, the debug branch is the live one. I need to merge that.)

If you have any questions about modifying WebPAC Pro, drop me a line. I also have a book coming out in May that walks you through creating JavaScript modifications for vendor tools, and I use the OPAC as an example quite often, walking through the changes and the code step by step.

[Edit: I posted a transcript of the talk.]

UX Lib was unlike any conference I've ever attended, and has been from the start. When I was asked to keynote, I was also put on the organizing committee (along with another of the keynoters, Paul-Jervis Heath). The idea was that we'd have a better understanding of the conference if we helped make it, and so we could create something bespoke for the event. I can say that I've never felt comfortable talking about phenomenology at a library conference before, but by working with the team that created and pulled off this unique event, I knew that this was my chance. (Not that I didn't panic, even up until 15 minutes beforehand, that this talk would be a flop. I rewrote it five times in the weeks before the event.)

Thankfully, this wasn't the case. Afterward, I received the highest compliment I've ever gotten for a talk: Andy Priestner, the committee chair, told me that he was so engrossed in what in was saying, that he kept forgetting to Tweet about it. (He'll deny that, of course, but Ned Potter made the mistake of putting that in writing in the last paragraph here, so I'm satisfied.)

[Edit: Donna Lanclos later called it "the best damn keynote talk I’ve ever attended," which made me blush and is crazy since she was at her own keynote a few days before.]

Of course, lots of folks did manage to tweet, and Ned Potter did a very kind writeup of the talk on his blog. I was also fortunate that the fantasically talented conference photographer, Jamie Tilley, did an incredible job of photographing the talk (as he did for the whole conference).

Photograph by Jamie Tilley Photography

I spoke about the difference between designing for tasks and designing for experience, and how the latter often looks remarkably like the former, but with some added emphasis on the types of emotions that doing a task might cause. But life is bigger than that. Emotions aren't just the by-product of doing things, and experience is more than just emotions and tasks. By exploring a few themes—the metaphors by which we understand technology, how phenomenology can help us learn about experience, how Heidegger saw our interactions with the world—I made the case for rethinking usability from the removal of problems to designing things that enable users to recover from the inevitable breakdowns that occur when things are used by people.

The conference was largely about immersing ourselves in UX—ethnographic research, ideation, prototyping, and selling our ideas. But one of the most amazing things that came out of UX Lib wasn't part of the official conference at all; it was a Twitter account that sprang up during the conference that helped explain UX in terms of stories that most folks are already familiar with: the world of Harry Potter. Cambridge's UX Lib was indeed a lot like @HogwartsUXLib, with the medieval buildings and grand halls and traditions. Sometimes it can be tough to talk about how UX plays out in our day-to-day work, but the genius behind @HogwartsUXLib manages to explain UX concepts like personas and ethnographic research by taking us out of our everyday and into something fantastic but familiar: the world of Hogwarts School for Witchcraft and Wizardry.

The account is so good at staying in character, and not just with clever things to tweet to the world. When my pal Matt and I got lost in Cambridge walking between venue spots, the best help we got was from @HogwartsUXLibs:

(In case you didn't notice, I'm suggesting that you just go follow the account on Twitter right now. Go on.)

I'm still digesting the experience of being at, participating in, speaking at, and down-right living UX Lib for a week, so there will be more to say. If you're interested in finding out more now, I have seen several wonderful write-ups for the conference. It was an experience that most of us who attended won't soon forget. (In fact, I've seen nearly as much twitter traffic today, 4 days after the conference ended, than when the conference was in full swing.) Check out these roundups (more will be added as I see them):

• Hit by the UX Libs Frieght Train by Andy Priestner
• UXLib 1: Georgina, The Wall! by Ned Potter
• UXLib 2: The Art of the Keynote: Matthew Reidsma by Ned Potter (blush)
• UXLib 3: The Art of the Keynote: Donna Lanclos and Paul-Jervis Heath by Ned Potter
• UXLib 4: Ethnography You Can Try at Home by Ned Potter
• UXLib 5: Ideation, Pitching, and Responsive Study Space ) by Ned Potter
• A New UXLib Community by Krista Godfrey
• UXLibs Skills & Tools by Krista Godfrey
• UXLib Conference Notes by Shelley Gullikson
• UXLib Conference Thoughts by Shelley Gullikson
• Cambridge is Strange by Andrew Asher
• It's a conference, Jim, but not as we know it. UXLibs, Cambridge 2015 by Jessica Stephens
• UXLibs: Part One: A Personal Reflection by Jenny Foster
• UXLibs: Part Two: Chop Down the Door by Jenny Foster
• UXLib – User Experience in Libraries by Carl Barrow
• UXLibs in Cambridge–Keynoting, Dining and Punting, Oh My by Donna Lanclos
• UX Libs: a very messy blog post by Helen Murphy
• The UX Libs Experience by Karine Larose
• More than Usable A transcript (of sorts) from my UXLibs Keynote.)