Over the past few weeks I’ve begun delving into much deeper analysis than I have in the past with more advanced tools and a much larger dataset. At present I have a database of over 10 million ReTweets and I’ve gained access to Twitter’s new streaming API which allows me to build a very large (10 million and growing) random sample of all tweets (not just ReTweets).

In re-visiting a data point that I looked at 6 months ago (this time with a larger data set), I found that in a random sample of normal (non-ReTweet) Tweets, 18.96% contained a link, whereas 3 times that many ReTweets (56.69%) included a link.

Then I tested the assumption that simplicity is a vital component of ReTweets (as it has been observed in other viral-content types) and I found that random Tweets have 1.58 syllables per word on average, while ReTweets had an average of 1.62 syllables per word. Longer, higher syllable-count words are typically more complex, indicating that ReTweets may be more complex than their less viral counterparts.

Comparing two different types of reading grade level analysis revealed that ReTweets, in general, are less “readable” and require a higher level of education to understand. A Flesch-Kincaid test gave ReTweets a reading grade level of 6.47 years of education, while random Tweets only required 6.04 years. The similar SMOG test (Simple Measure of Gobbledygook) indicated that ReTweets required 6.13 years of schooling, with random Tweets only needing 5.88 years.

 
Another characteristic commonly found in viral content is novelty; that is, the “newness” of the ideas and information presented. I created a measure of novelty by counting how many other times each word in my sample sets occurred. In the random Tweet sample, each word was found an average of 89.19 other times, while in the ReTweet sample each word was only found 16.37 other times. This shows us that while simplicity may not be very important to ReTweetability, novelty certainly is.

 
Part of speech (POS) tagging is an analysis technique in which an algorithm is used to label each word in a piece of content as a specific part-of-speech–noun, verb, adjective, etc. The graph below shows what percentages of words in each sample were labeled as a specific part-of-speech. It lists only the most interesting parts from the much larger list of POS tags.

Interesting points from this data include the noun and 3rd-person heaviness of ReTweets, indicating a subject matter and headline type nature.

 
I also used the two linguistic lexicons currently in use on TweetPsych: RID and LIWC.

First up is the more “Freudian” Regressive Imagery Dictionary (RID). This coding scheme is designed to measure the amount and type of three categories of content: primordial (the unconscious way you think, like in dreams); conceptual (logical and rational thought); and emotional.

Significantly more primordial content has been found in the poetry of poets who exhibit signs of psychopathology than in that of poets who exhibit no such signs (Martindale, 1975).

The first RID graph shows that ReTweets contain less primordial and emotional content than random Tweets and more conceptual content.

 
Looking at specific RID codes, we see that social and instrumental (constructive words like build and create) behavior are ReTweetable, while abstract thought and sensation-based words are not.

 
The last analysis I performed used LIWC (pronounced “Luke”). This is a lexicon similar to RID, but based in more reviewed and accepted research and refined over 15 years. LIWC measures the cognitive and emotional properties of a person based on the words they use.

In order to provide an efficient and effective method for studying the various emotional, cognitive, and structural components present in individuals’ verbal and written speech samples, we originally developed a text analysis application called Linguistic Inquiry and Word Count, or LIWC.

LIWC analysis shows that Tweets about work, religion, money and media/celebrities are more ReTweetable than Tweets about negative emotions, sensations, swear words and self-reference.

People That Think Like You

When you generate a profile for yourself or someone else, TweetPsych will also show you a list of 5 users who it believes share similar psychological characteristics. This matching is not done topically, therefore the other users you’re presented with may not Tweet about the same things as you.

These users come only from the list of users that the system has analyzed so far, so the results will get better as it analyzes more accounts. Starting this week, I am automatically profiling accounts starting with a few prioritized lists, including most ReTweeted users and most followed users to help build a large dataset for comparison.

Site Profiling

The second feature I added this weekend is site profiling. When you enter a URL TweetPsych will create a psychological profile of the content on that page and match it against its database of user profiles, returning the 50 closest matches.

Again, this matching is not done on a topical basis, meaning the users presented might not tweet about the same subjects the page is about. The goal is to help you find users that may be mentally aligned with the psycho-graphic profile of the web page you provided.

And just to reiterate, TweetPsych is still beta stuff and I’m aware there are issues, specifically around explaining and presenting the features in a more understandable way, but my first priorities were making the system stable under the huge traffic load (and my host MediaTemple has been awesome helping me) and fleshing out the potential power of the technology. I’m very open to new feature suggestions as I continue working on TweetPsych.

I am contemplating the possibility of releasing an API but I’m still thinking about how to handle the possibly high server resource demands. What features would you like to see in an API?

Communication is a window into a person’s mind, and the way a person talks can tell you a lot about how they think. Linguists have developed two methods to decoding the written word into a meaningful profile of a person’s cognitive processes.

One method is called the Regressive Imagery Dictionary (RID). This coding scheme is designed to measure the amount and type of three categories of content: primordial (the unconscious way you think, like in dreams), conceptual (logical and rational though) and emotional.

Significantly more primordial content has been found in the poetry of poets who exhibit signs of psychopathology than in that of poets who exhibit no such signs (Martindale, 1975). There is also more primordial content in the fantasy stories of creative as opposed to uncreative subjects (Martindale & Dailey, 1996), in psychoanalytic sessions marked by therapeutic “work” as opposed to those marked by resistance and defensiveness (Reynes, Martindale & Dahl, 1984), and in sentences containing verbal tics as opposed to asymptomatic sentences (Martindale, 1977). A cross-cultural study of folktales from forty-five preliterate societies revealed, as predicted from the “primitive mentality” hypothesis of Lévy-Bruhl (1910) and Werner (1948), that amount of primary process content in folktales is negatively related to the degree of sociocultural complexity of the societies that produced them (Martindale, 1976). Martindale and Fischer (1977) found that psilocybin (a drug that has about the same effect as LSD) increases the amount of primordial content in written stories. Marijuana has a similar effect (West et al., 1983). Research has also revealed more primordial content in verbal productions of younger children as compared with older children (West, Martindale, & Sutton-Smith, 1985) and of schizophrenic subjects as compared with control subjects (West & Martindale, 1988).

The other method is Linguistic Inquiry and Word Count (LIWC). In development for over 15 years, the LIWC measures the cognitive and emotional properties of a person based on the words they use.

In order to provide an efficient and effective method for studying the various emotional, cognitive, and structural components present in individuals’ verbal and written speech samples, we originally developed a text analysis application called Linguistic Inquiry and Word Count, or LIWC.

I’ve combined these two systems with a Porter stemming algorithm and my own Twitter analysis infrastructure to create TweetPsych.com.

TweetPsych uses the LIWC and RID to build a psychological profile of a person based on the content of their Tweets. It compares the content of a user’s Tweets to a baseline reading I’ve built by analyzing an ever-expanding group of over 1.5 million random Tweets, then highlighting areas where the user stands out.

The service analyzes your last 1000 Tweets; as such, it works best on users who have posted more than 1000 updates. It is also better suited for running analyses on accounts that are operated by a single user and use Twitter in a conversational manner, rather than simply a content distribution platform. It takes a few moments to analyze an account the first time, but subsequent views of a profile will load faster.

I’ve tried to translate the codes that come from the two linguistic systems into more meaningful explanations, but I may have missed a few. I will continue to expand these definitions, while also refining the system and algorithm to better analyze Twitter-specific content.

I think the possibilities of a system like this are enormous, from matching like-minded users to identifying users that exhibit certain useful or desirable traits. I’d love to hear your thoughts on where this could be improved or where I could take this technology next.

I’ve studied characteristics from pre-web memetic channels (like urban legends, rumors, slang, oral tradition and proverbs) and many of the traits I found there I’ve also found when looking into ReTweets. Namely concepts like communal recreation, social proof, information cascades, knowledge gaps, novelty and utility.

I’ve found myself telling the Snow Crash story a lot recently to explain what I see as the true power of what I call viral marketing science. Here’s two versions of it.

Being that I come at this opportunity from a marketing background, I look to this analysis to build a framework for repeatably creating contagious memes, so this presentation from PubCon Austin aims to do just that for ReTweets.

I looked at the roughly 200 suggested users and compared them to the 200 most followed users not on the list. Since many of the suggested users are the most followed people on Twitter, they had a much higher average number of followers.

However when I looked at the average number of Tweets-per-Day (TpD) posted by suggested users versus non-suggested top users, I found that non-suggested users tended to Tweet a bit more frequently.

Then I started looking at ReTweets-per-Day (RTpD) and found that since they have so many more followers, suggested users are ReTweeted somewhat more often.

To control for the difference in follower counts, I then calculated each user’s number of ReTweets-per-Day (RTpD) divided by the number of followers they had and found that non-suggested users tend to have more ReTweets-per-Follower (RTpF), meaning they have, on average more ReTweet-friendly followers.

I then calculated my favorite ReTweet metric, ReTweetability. That is the number of ReTweets-per-Day divided by the number of Tweets-per-Day over follower counts.

This is designed to control not only for differences in follower numbers, but also for differences in tweeting-frequency to show just the “virality” of their content and their followers. (I’ve written about this metric before.)

The result is clear, suggested users are far less ReTweetable. I think this is likely due to the fact that many of the followers gained by those users on the suggested list are new Twitter users and may be less ReTweet-savvy.

Some users blog about ideas and links they first saw on Twitter and for marketers this represents a huge opportunity for traffic generation, buzz building and link development. The first piece of data to look at is how often people action blog about tweets:

Then I looked at what type of content average users blog about from Twitter as well as what types of content “frequent twitter-to-bloggers” blog about. I defined frequent as once a week or more and 21.57% of my data set fell into that category.

1 Seed Selection

First emerging near the very densely populated Mexico City, Swine Flu seemed to travel to half a dozen other countries around the world over night. Many of the first confirmed cases were among children in schools who had taken trips to the popular Mexican vacation destination.

Children, due to their gregarious nature and low levels of hygiene awareness, are called the “super spreaders” of this outbreak, prompting many schools to close. Children are often blamed for a host of illnesses, but perhaps the most famous super spreader was Typhoid Mary, a cook who was responsible for 2 outbreaks of typhoid fever in the early part of the 1900s.

When planning to seed a viral marketing campaign it is important to take into account which members of the target audience have the most potential to be contagious. Typically, savvy social media users, including bloggers, Twitter users, Diggers and Facebook fanatics, are the best seeds.

2 Knowledge Gaps

A phenomenon I first noticed when reading a World War II era research paper by the CIA-precursor, the OSS, discusses the spreading of information when knowledge about a particular topic is scarce.

The OSS paper says that good rumors are “provoked by” and provide interpretation or elaboration on a current event, filling a “knowledge gap.” If the locals heard a big boom earlier in the day, a rumor could easily be constructed to explain it if the authorities did not.

In the absence of official or authoritative information, rumors proliferate. The CDC has actually been pretty good at communicating authoritative information about Swine Flu, but in those pockets where people are unaware of it, lots of “theories” and “facts” have emerged. For example, some countries have banned imports of pork products, despite the fact that meat cannot carry the Swine Flu virus, h2N1.

3 Addition vs Replacement

Because the common name “Swine Flu” misrepresents the origin and dangers of the virus (and does not conform to historic convention of naming influenza outbreaks for the geographic region they first emerged from), several organizations have tried to “rename” it, but none have taken hold in the public discourse.

Each of us has a mental framework of ideas built on each other that we use to view and understand the world around us. When we are exposed to a new meme that contradicts an existing portion of our framework, it is very difficult for the new idea to replace the old idea. It is much easier for us to assimilate new ideas that either agree with or expand on our existing mental frameworks. Think of an under-construction brick house: it takes much more effort to replace a previously laid brick with a new one than it does to begin building an addition onto the house with the new bricks.

4 Novelty

One of the factors that makes this version of the swine flu so dangerous is that it is a novel combination of several genetic sources for which humans have built up no natural immunity and for which no vaccines exist. The 2009 version of the h2N1 virus is essentially a remix of previously existing strains and may form the bridge by which the most virulent forms of human, bird and swine flus can merge and co-evolve.

In the study of applied memetics, we learn that one of the requirements for a successful meme is that it possess some form of novelty. It is often easiest to achieve easily understood novelty by putting new content in an old structure, or putting old content in a new structure.

5 Communal Recreation

Viruses evolve like a giant game of “telephone,” as each host that becomes infected with a particular strain offers the pathogen a chance to evolve into a new variety. This means that the Swine Flu is rapidly morphing and multiple strains probably already exist. The higher mortality rate in Mexico may be due to a more deadly version having evolved there that hasn’t yet spread abroad.

In urban legends, rumors, slang and many other forms of social communication, each person who is exposed to a particular meme creates their own version of it before passing it on, often fitting it to their personal and societal frameworks, thereby making it more adept at spreading in their community. Therefore, successful campaigns must allow and encourage remixing by their target audiences.

6 Infectious Period Length

The period of time from infection to non-contagiousness of a pathogen is known as it’s “infectious period.” This is when the person is a potential seed for the virus. The CDC has defined Swine Flu’s infection period as:

Infectious period for a confirmed case of swine influenza A (h2N1) virus infection is defined as 1 day prior to the case’s illness onset to 7 days after onset.

The longer the infectious period lasts, the more secondary cases may result from an un-quarantined primary case.

In the case of most viral and social marketing campaigns, the infectious period exists as an event rather than a period of time. An “infected” person will blog or Tweet about something. The goal for viral marketers looking to exploit the infectious period should then be to increase the number of infectious events each individual will undertake.

7 Endemic vs Epidemic

In mathematical models of epidemiology, there are 2 concepts of the “state” of the spread of a “successful” pathogen: endemic steady state and epidemic. Assuming a population with zero immunity (because this outbreak is a novel h2N1 strain, no one has any natural immunity to it yet), an endemic state indicates that each infected person infects exactly 1 other person; an epidemic state indicates that each case will cause multiple cases. The steady state means that the outbreak will continue to spread without external influences. Viruses that enter the epidemic state will eventually either die out due to exponential growth or reach the endemic steady state.

In viral marketing, we must strive to understand and improve the reproduction rate of our campaigns. We can assume zero immunity because, except in certain rare cases, people aren’t immune to most ideas. With social marketing, however, we tend to see a reproduction rate of far under 1, that is each “infected” person will infect less than 1 person on average. This has lead to research into extending the total reach of a meme through “big seeding,” but when you model total campaign spread as a function of seed size and reproduction rate, it is much more effective to increase the reproduction rate. As marketers, it is crucial to encourage each user to spread the campaign to as many other users as possible, rather than try to “seed” it with huge numbers of initial users.

First up is Convergence 2009 in Vancouver on May 11th. I’ll be talking about the intersection of web search and social media.

Then I’m headed to WordCamp Mid Atlantic on May 16 in Baltimore. I’ll be talking about integrating WordPress with Twitter and other social media sites.

Then, on May 26 and 27, I’ll be in Mountain View California speaking at the 140 Twitter Conference. The panel(s) I’m on and topics are TBD.

Finally,  June 8 through June 10 I’ll be in Toronto at SES discussing which social web signals search quality engineers might be looking at to determine a site’s authority.

If you’re planning to go to any of these conferences, please come say hi.

I’ve had most of this code written for quite a while, but I’ve been too busy to finish it enough to release it. So I pulled out some of the basic functionality and made a little teaser version just to see what everyone thinks about it.

This version of the tool allows you to enter the URL of a page or blog post you’d like to have ReTweeted and receive suggestions of highly ReTweetable related words to add to your content and use when Tweeting said content.

The full version will show you those users who are the most ReTweetable when it comes to content related to yours. It will also allow you to schedule Tweets to be posted during the most ReTweetable times and days, as well as “seeding” your content via DM to those ReTweetable users who have given you permission to DM them. Once your Tweet goes out, the system tracks ReTweets and clicks it gets, thereby allowing you to test and refine your content further.

So go check it out and let me know what you think.

In that week, over 900 votes were cast; 13 participants earned the requisite 20 credits (or more) and became certified scientists.

The winner, Wombat5277 received 166 credits in under a week and had this to say about winning:

Being named the top Viral Marketing Strategist in my class is without a doubt the highest honor I have ever received. I make an oath to only use my new IVMS status for the betterment of my fellow man. Thank you.

If you want to follow some top quality viral marketing scientists, check out our entire 2009 class:

There are a bunch of other people and companies doing great research and work into this kind of marketing, but they are the minority.

I decided that the best way to bring the science of viral marketing closer to its full potential was to start training the next generation of scientists. So I am proud to present to you IVMS: The Institute for Viral Marketing Science.

 

IVMS offers a six class certification course that will give students the foundational knowledge to begin pursuing viral marketing science in their own directions. The first cycle starts in June, and to keep class sizes small, we can only accept the best and brightest applicants. If you're interested in becoming a viral marketing scientist, head on over now and enroll.

]]> http://danzarrella.com/introducing-the-institute-for-viral-marketing-science.html/feed http://danzarrella.com/introducing-the-institute-for-viral-marketing-science.html http://feedproxy.google.com/~r/DanZarrella/~3/BcBkTzg0J5o/catch-me-on-clickz-webinar-on-twitter-tomorrow.html http://danzarrella.com/catch-me-on-clickz-webinar-on-twitter-tomorrow.html#comments Mon, 30 Mar 2009 20:02:14 +0000 Dan Zarrella http://danzarrella.com/?p=1321 Just wanted to post a quick note to let you know that you can listen to me talk tomorrow on a free webinar from ClickZ on "Twitter for Business." I'll be presenting some of my ReTweeting data, as well as other research-based advice on the best ways to use Twitter. So go register for the webinar and tell everyone you know to come to it too!]]> Just wanted to post a quick note to let you know that you can listen to me talk tomorrow on a free webinar from ClickZ on “Twitter for Business.” I’ll be presenting some of my ReTweeting data, as well as other research-based advice on the best ways to use Twitter.

So go register for the webinar and tell everyone you know to come to it too!

]]> http://danzarrella.com/catch-me-on-clickz-webinar-on-twitter-tomorrow.html/feed http://danzarrella.com/catch-me-on-clickz-webinar-on-twitter-tomorrow.html http://feedproxy.google.com/~r/DanZarrella/~3/p-AtS2XM4ig/viral-marketing-blog-reading-list.html http://danzarrella.com/viral-marketing-blog-reading-list.html#comments Thu, 26 Mar 2009 14:44:50 +0000 Dan Zarrella http://danzarrella.com/?p=1318 Viral Marketing Alltop and would love if you took a look at it and then let me know...]]> I love what Guy Kawasaki is doing with Alltop (especially since I’m listed there) and they recently launched My Alltop, where you can create your own “magazine rack” of blogs.

I’m always looking for more great blogs to read, especially about viral marketing, so let’s use Alltop to crowdsource the creation of a viral marketing blog reading list.

I created a Viral Marketing Alltop and would love if you took a look at it and then let me know here in the comments what blogs I’m missing.

]]> http://danzarrella.com/viral-marketing-blog-reading-list.html/feed http://danzarrella.com/viral-marketing-blog-reading-list.html http://feedproxy.google.com/~r/DanZarrella/~3/kAALsLSSSAI/viral-marketing-science.html http://danzarrella.com/viral-marketing-science.html#comments Tue, 24 Mar 2009 16:48:32 +0000 Dan Zarrella http://danzarrella.com/?p=1297 I tend to look at social and viral marketing on a campaign level, evaluating viral marketing campaigns as a whole instead of individual components. For me, viral marketing science is all about figuring out what and how things spread, as opposed to the more general "how communities interact online," and so the science comes in when various elements are interacting with each other and with the audience. It is important to note that this does...]]>
I tend to look at social and viral marketing on a campaign level, evaluating viral marketing campaigns as a whole instead of individual components. For me, viral marketing science is all about figuring out what and how things spread, as opposed to the more general “how communities interact online,” and so the science comes in when various elements are interacting with each other and with the audience.

It is important to note that this does not mean that viral marketing is purely tactical; on the contrary, there is a great deal of strategy present in how these campaigns fit into a brand’s overall marketing mix. The science is in hitting the sweet spot between viral tactical elements and overarching marketing strategy.

The fields I draw from commonly include sociology, neurology, statistics, history, psychology (especially of the evolutionary type), economics, biology and memetics. I also use metaphors, terms and models from epidemiology as tools to help communicate about viral marketing, as these are much more commonly understood.

I see much of the information currently available about social and viral marketing as being comprised of two distinct types: conjecture-driven and data-driven. The former is the majority, a formulation of advice based on anecdotal evidence and “what seems right.” My work with multivariate testing, combined with research from The Tipping Point and Freakonomics, has shown me that the actual data often disproves the conclusions drawn purely from gut-feelings. My efforts have focused on creating content that is backed by facts, not feelings, and falls into the data-driven bucket. I call it viral marketing science.

The first thing that got me thinking about the potential power of scientific viral marketing was, surprisingly, a work of fiction: Neal Stephenson’s Snow Crash. In it, the villain creates a biolingusitic virus based on a prototypical, brain-stem related Sumerian language. He uses the virus to basically enslave a whole bunch of people in a world domination plot.

I also believe that there is plenty of room for art in viral marketing; the creativity, intuition and improvisation involved in a successful campaign often come from a deep understanding of the data involved. But the brute creative genius most people assume is the core of contagious campaigns can make the entire exercise seem like black magic and entirely unpredictable. However, using scientific methods, it is possible for mere mortals to create repeatably viral campaigns.

]]> http://danzarrella.com/viral-marketing-science.html/feed http://danzarrella.com/viral-marketing-science.html http://feedproxy.google.com/~r/DanZarrella/~3/1nLLRtZeDA4/alex-bogusky-whats-wrong-with-retweets.html http://danzarrella.com/alex-bogusky-whats-wrong-with-retweets.html#comments Tue, 10 Mar 2009 13:56:23 +0000 Dan Zarrella http://danzarrella.com/?p=1262 Crispin Porter + Bogusky, or CP+B as those in the know like to say, a large advertising agency best known for edge-pushing viral marketing. As such, they're also one of the few ad agencies whose work I admire. CP+B has won a slew of awards; they were recently named Creativity's Agency of the Year and have collected a handful of One Club Pencils in just a few years. After a short stint on Twitter, Alex publicly...]]> Alex Bogusky is co-chairman of Crispin Porter + Bogusky, or CP+B as those in the know like to say, a large advertising agency best known for edge-pushing viral marketing. As such, they’re also one of the few ad agencies whose work I admire. CP+B has won a slew of awards; they were recently named Creativity’s Agency of the Year and have collected a handful of One Club Pencils in just a few years.

After a short stint on Twitter, Alex publicly quit the micro-blogging service, saying it “wasn’t for him.” Intrigued by his thoughts on ReTweeting, I asked him to do an email interview.

Dan Zarrella: I’m a huge fan of the viral work CP+B has done, especially for Burger King (most famously the Subservient Chicken and most recently the Whopper Sacrifice). You guys seem to be using new mediums and platforms to build these campaigns. Have you used Twitter like this yet, or do you have any plans to?

Alex Bogusky: That’s really kind of you to say. We just love interacting with consumers instead of talking at them. We love the back and forth. We’re playing around a little bit with the Old Navy Supermannequins. Just getting going but it should get interesting soon.

DZ: Do you think Twitter has reached a critical mass yet where big brands are well served by engaging the audience there?

AB: I don’t know the raw numbers for twitter but there are certainly some big wins to be had. But we can’t really look at any social media in isolation because they’re all bouncing off one another and influencing each other in real time.

DZ: To me ReTweeting is an incredibly open and powerful viral messaging mechanism. Do you think ReTweeting is going to be an important tactic for viral marketing in the future?

AB: It could be. It’s certainly faster at garnering more eyeballs than e-mail, IM or chat. The question will be does it amplify or simply speed up the process. Right now we have no way of knowing because it hasn’t got the adoption yet.

DZ: You and Chris Anderson (among others) have recently expressed concern with the carefree and often intent-changing way in which the tweets you post are ReTweeted. My understand is that the core problem is that if someone else ReTweets your content, but rewrites it, it may appear that you’ve said something you haven’t. Is this a big enough problem to make you weary of ReTweeting as a marketing form?

AB: This is my personal issue with retweeting and it makes me personally uncomfortable. As a marketer I don’t see it as a concern. You want people to put their stamp on marketing even if it seems negative. Consumers play rough and you have to let them play. But as a consumer I would be concerned that somebody can appear to be putting your thoughts forward but in fact they have changed them. Maybe even reversed them. It seems like it would benefit the service to somehow lock the original message if it is presented as a RT.

DZ: What do you think is the most exciting and/or important thing about Twitter for viral marketing going forward? (Is there anything exciting or important?)

AB: I don’t like to approach new media as a marketer. I prefer to approach it as a consumer and that appreciation is more likely to inspire thinking that might help our clients. Like any new media there will be significant resistance to marketing/advertising. That was a huge them with Subservient Chicken. It was actually the first hyper successful marketing foray into the web and it pissed a lot of people off. We can expect some of the same here. Twitter will also put off integrating marketing into the service for as long as possible to get the raw numbers up and the behavior fully adopted. But at some point to monetize they will probably look to advertisers. So I think we can expect the tools that marketer have at their disposal to increase in the same way it did with Google. It may all be fairly invisible to the user ala adwords but the ability to monitor and jump into real time conversations will have tremendous appeal. I’m a little skeptical of its actual value or to put it more accurately I think this opportunity will be overvalued in the beginning in much the same way banners were overvalued in the beginning and then saw that value plummet. But I’m not a futurist. Specifically because I’ve been around long enough now to see that most predictions don’t pan out. What I like about twitter is what’s happening right now and what will be happening in the next fifteen minutes. It’s extremely exciting.

]]> http://danzarrella.com/alex-bogusky-whats-wrong-with-retweets.html/feed http://danzarrella.com/alex-bogusky-whats-wrong-with-retweets.html http://feedproxy.google.com/~r/DanZarrella/~3/gIXYbgKn4r8/introducing-the-retweetability-index.html http://danzarrella.com/introducing-the-retweetability-index.html#comments Tue, 03 Mar 2009 15:01:50 +0000 Dan Zarrella http://danzarrella.com/?p=1212 And I've created a new site that allows you to do just that: ReTweetability.com. The site has a list of the most ReTweetable users, as well as a search feature that allow you to find the most contagious users Tweeting about various topics. There are 3 major areas where Twitter users can affect the number of ReTweets they...]]> If we want to be able to create contagious Tweets, we have to know what contagious Tweets look like. And I’ve created a new site that allows you to do just that: ReTweetability.com.

The site has a list of the most ReTweetable users, as well as a search feature that allow you to find the most contagious users Tweeting about various topics.

There are 3 major areas where Twitter users can affect the number of ReTweets they get:

• Followers
• Tweeting Volume
• Contagiousness of Content

We know what “more followers” and “more Tweets” look like, providing well-defined targets in those areas, but, until now, there has been no standard measurement of contagiousness.

I’ve looked into the effect that a user’s number of followers and content of their Tweets had on the level of ReTweeting that occurred. Predictably, the number of followers you have will get you more ReTweets, but the correlation isn’t as strong as expected. Certain patterns of common words and phrases do emerge.

Lists that rank users by the simple number of times they are ReTweeted are not displaying a list of those users with the most ReTweetable content. If a user has a large number of followers, or posts a huge amount of content, naturally they’re going to get more ReTweets; however, it is important to note that this is not due to how contagious his or her Tweets were.

What I’m trying to do with the ReTweetability metric is begin to develop a simple formula upon which the infectiousness of a user’s content can be measured. This algorithm would eliminate the effect of the user’s follower count and Tweeting rate.

 

 

The ReTweetability metric I’m using for the index right now is based on the natural logarithm of both the followers and Tweets per day numbers. This is done to compress the range of variation in both numbers, while acounting for the power law shaped graph displayed by the distributions of the two variables.
Prior to using the logarithm, the formula over-penalized users with higher than average followers (around 100) and Tweets per day (around 5), which turns out to be most users.

I’ve also explored the possibility of using the square root of the 2 values; this produces a range smaller than without using the natural logarithm, but larger than with it. I would love to have a discussion about the correct method for this, and I expect some variation in the formula here.

Due to the extremely small result of the formula, I’ve had to multiply it by 10,000,000 to enhance its readability — I would also love feedback on this.

]]> http://danzarrella.com/introducing-the-retweetability-index.html/feed http://danzarrella.com/introducing-the-retweetability-index.html http://feedproxy.google.com/~r/DanZarrella/~3/R5Al-wXt9p0/prototyping-for-viral-marketing.html http://danzarrella.com/prototyping-for-viral-marketing.html#comments Fri, 27 Feb 2009 14:51:21 +0000 Dan Zarrella http://danzarrella.com/?p=1163

"When the number of factors coming into play in a phenomenological complex is too large scientific method in most cases fails. One need only think of the weather, in which case the prediction even for a few days ahead is impossible." -Albert Einstein

You can't predict viral marketing. You also can't guarantee something will "go viral," then again, neither can you promise organic SEO results to a client. With search marketing there are...]]>

“When the number of factors coming into play in a phenomenological complex is too large scientific method in most cases fails. One need only think of the weather, in which case the prediction even for a few days ahead is impossible.” -Albert Einstein

You can’t predict viral marketing. You also can’t guarantee something will “go viral,” then again, neither can you promise organic SEO results to a client. With search marketing there are best practices and analysis methods and tools. On the other hand, viral marketing doesn’t (yet) have these sort of guidelines to produce repeatable and sustainable results.

What we can do however, is to model our viral marketing ideas and campaigns from prototypical characteristics of historically contagious content. In biological evolution, successful genes arise by way of mutation from slightly-less successful ancestors.

If you look at past campaigns that had similar content, media and/or audience to your goals, common traits would emerge. These traits can be used as guidelines for future campaigns.

The patterns emerge from the selection pressures applied by the audience and media. If your audience is all on one type of platform, that environment imposes a unique set of pressures that determine which content is successful.

Twitter is a great petri-dish for analyzing viral content like this. A Twitter environment selects for short and simple ideas and powerful calls to action, whereas an email environment selects for strong sender-receiver relationships.

On the broad topic scale represented in ReTweets, useful patterns have already emerged, the most obvious example of which is “please retweet.”

Social news sites are another great place for modeling research, in fact most good internet marketers can tell you all about what structure of content do well on Digg, delicious, reddit, etc. The same holds true for most niches of the blogosphere.

Every email you get forwarded by someone is a potential prototyping source, this is especially true if you’re getting emails from the audience you’re trying to reach. Social networks could be a powerful source of information, but due to privacy concerns much of it is not readily available.

An important caveat here is novelty. In most forms of viral content, the newness and uniqueness of the idea is a vital component. In many places I’ve found a New/Old (inspired by Clotaire Rapaille) structure where either new content is put into a old structure, or old content is put into a new structure. An example of the former is “trackbacks for Twitter” and an opposite example is “cat pictures with lolspeak”.

]]> http://danzarrella.com/prototyping-for-viral-marketing.html/feed http://danzarrella.com/prototyping-for-viral-marketing.html http://feedproxy.google.com/~r/DanZarrella/~3/qwuh4Wz2dcg/retweet-etiquette.html http://danzarrella.com/retweet-etiquette.html#comments Fri, 20 Feb 2009 15:37:15 +0000 Dan Zarrella http://danzarrella.com/?p=1153 This post was inspired by a conversation I had with TED's Chris Anderson. I'm not a big fan of "rules" for social media, but in certain circumstances it does make sense to conform to a certain community-set convention. With the existence of several ReTweet counting services and my ReTweet mapper, a certain regular format can also help make sure your ReTweets are counted and analyzed. Etiquette in social media is also pretty important, as it can...]]> This post was inspired by a conversation I had with TED’s Chris Anderson. I’m not a big fan of “rules” for social media, but in certain circumstances it does make sense to conform to a certain community-set convention. With the existence of several ReTweet counting services and my ReTweet mapper, a certain regular format can also help make sure your ReTweets are counted and analyzed. Etiquette in social media is also pretty important, as it can help ensure that everyone gets along nicely.

TweetDeck has a ReTweet button so it has defined a kind of de facto standard format for ReTweets. It then places the cursor at the end of the tweet so many people add their own thoughts there.

RT @username: Original Tweet [Your Take]

Here are also some good rules of thumb to remember when ReTweeting:

1. Do not start the ReTweet with an @ sign, as this will mean that generally only people following both you and the person you’ve @’d will see the ReTweet, defeating its purpose of increased reach.
2. Try to credit at least the original Twitterer who posted the Tweet. If you have room, also try to credit the person who’s ReTweet you saw.
3. The most common ReTweet format is RT: @username. Typically this is reserved for the original poster. A good way to credit the person who’s Tweet you saw, try adding (via @username) to the end of the tweet.
4. If the original tweet included a call-to-action (like “please ReTweet”) try to keep that in your ReTweet, if you have enough room.
5. If the original tweet has a link in it, keep it there. Also, try not to re-shorten the link using another service.
6. If the original tweet has a hashtag, try to use it in your ReTweet as well (if you have room).
7. Try to keep as much of the original tweet intact as possible, but it is acceptable to add your take on it (especially at the end, in parenthesis)

Did I miss anything? Do you have any ReTweet pet peeves? Let me know in the comments below.

]]> http://danzarrella.com/retweet-etiquette.html/feed http://danzarrella.com/retweet-etiquette.html http://feedproxy.google.com/~r/DanZarrella/~3/Ui_3J2sMdY8/viral-thinking-a-practical-framework-for-viral-marketing.html http://danzarrella.com/viral-thinking-a-practical-framework-for-viral-marketing.html#comments Wed, 18 Feb 2009 16:01:32 +0000 Dan Zarrella http://danzarrella.com/?p=1135 design thinking I've been thinking about a practical framework for creating social media and viral marketing campaigns. I think one of the most important steps in this process is the "Research" phase. When I started thinking about this process, I used a metaphor from genetic engineering: If I wanted to construct the most infectious biological virus possible, I would start with the most contagious existing...]]> Inspired by David Kelly’s work on design thinking I’ve been thinking about a practical framework for creating social media and viral marketing campaigns.

I think one of the most important steps in this process is the “Research” phase. When I started thinking about this process, I used a metaphor from genetic engineering: If I wanted to construct the most infectious biological virus possible, I would start with the most contagious existing pathogens and work off of them. You might also study the spread of epidemics to identify the most important vectors. So in Viral Thinking, I’m suggesting that you model your campaigns off of those campaigns, ideas and memes that are relevant to your goals and have proven themselves to be viral.

Here’s my first attempt at it, I’d publishing this as a rough draft to get as much feedback as possible.

1. Define
1. What are the goals of your campaign
2. Who is your target audience
2. Research
1. Identify relevant successful memes
2. Identify relevant influential vectors and individuals
3. Identify “information gaps” in your target audience
3. Brainstorm
1. Brainstorm many possible campaigns
2. Brainstorm many possible seeding tactics
4. Check
1. Check your campaign ideas for “viral ingredients“
1. Novelty
2. Simplicity
3. Social Proof
4. Utility
5. Communal Recreation
6. Incentive
5. Build
1. Build out several of the best campaigns
2. Test these campaigns with a small portion of your target
1. Refactor them as necessary to maximize the “that’s awesome” responses
6. Seed
1. Launch your campaign via as many seeding tactics as relevant
7. Monitor
1. Measure campaign analytics against your goals
2. Monitor your target audience’s reaction to your campaign
3. Refactor the campaign to respond to feedback where necessary
8. Learn
1. Identify lessons learned from each campaign
2. Implement lessons learned in each successive campaign

Again, I’m posting this to get your thoughts on this process, especially how it could be better and more concrete and practical.

]]> http://danzarrella.com/viral-thinking-a-practical-framework-for-viral-marketing.html/feed http://danzarrella.com/viral-thinking-a-practical-framework-for-viral-marketing.html http://feedproxy.google.com/~r/DanZarrella/~3/fTjVujTf5oo/viral-tweeting-survey.html http://danzarrella.com/viral-tweeting-survey.html#comments Mon, 02 Feb 2009 14:30:44 +0000 Dan Zarrella http://danzarrella.com/?p=1128 survey. Similar in design to my Viral Content Sharing Survey, this brief questionnaire consists of 17 questions and should only take about 5 minutes to complete. The data gathered from just a few minutes of your time will allow me to continue to explore why and how ReTweeting happens. Please, help me further my research into viral messaging and the...]]> To gather more data about how viral messaging spreads through Twitter, I’m launching a short survey. Similar in design to my Viral Content Sharing Survey, this brief questionnaire consists of 17 questions and should only take about 5 minutes to complete. The data gathered from just a few minutes of your time will allow me to continue to explore why and how ReTweeting happens.

Please, help me further my research into viral messaging and the impact of Twitter on content sharing by taking this quick survey; then, share it with your Twitter friends by ReTweeting this link (http://tinyurl.com/baxdek).

Once I have a sufficient number of responses, I’ll analyze the data and publish a report on my findings. I anticipate that the survey will run for about a week or two in order to gather enough responses for scientifically sound data.

I need at least 1000 responses to extrapolate any measurable results, hopefully before the Twitter buzz dies down, so please take a minute to complete the survey and pass it on to a few friends, and keep checking back to see what I find. Thanks!

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