This story doesn't make it on to Google News front page or even their page of world news. It's not on the BBC's front page or in its European news section. Could be quite simply due to the fact that Reuters got the news late and everyone has moved on, but I see an article on HuffPo on this (from the same source) posted 3 hours ago.

I just noticed on the d8taplex news page that this article, entitled 'Starbucks to sell alcohol in some U.S. cafes' just hit 11, 430 clicks on bit.ly. This is an order of magnitude more than most articles get to in terms of bit.ly clicks.

Because the d8taplex page links to the Twitter accounts of the journalists when they are available, I took a look at what Alastair Sharp was sharing on Twitter. Alastair provides a couple of tweets on the topic, including a link to a video interviewing the new CEO.

I'll figure out a way to integrate recent tweets from the journalists into the interface in the near future.

Here we see that from the pool of recent articles with CJ's name on, one has made it to the hot column, while nine are still in probation looking for some clicks.

Over time, we will likely see articles move from the right to the left while new ones populate the unloved column.

By filtering on country names, or other keywords, one can get a sense of where attention is being paid.

1. Why are some news articles picked up and others not? News sources such as Reuters create articles that are either directly consumed or which are picked up by other publications and passed along.
2. Who are these people writing these articles? What are their interests, areas of expertise and personalities?
3. What is the role of the editor and how do they influence the selection and form of the content produced by the news machine?

The next round of experimentation with news aggregation has resulted in the current new site. It has the following features.

Firstly, it presents two lists of articles. On the left, are those articles which are currently getting a reasonable amount of buzz (as determined by bit.ly clicks). The second column, on the right, presents those articles which are not yet receiving much attention. As you read the left you will probably realise that you are already familiar with these stories.

The amount of bit.ly juice is indicated by the number prefixed by 'B:' The article block consists of the title, the time stamp of the article, the link and the list of contributors.

Secondly, by providing the dynamic filtering one can very quickly get a view of which unloved articles are present relating to those stories that are already getting attention. For example, in the screenshot below we can see that one article about Gingrich is getting buzz while four others that mention him are languishing on the right.

Thirdly, it connects the user with the personality of the author and editor by providing, where possible, various facets of information such as job title, twitter account, email address, phone number, role, languages spoken, etc. Some of these are gleaned from the Reuters site while others are mined from various social network sites and so on.

Please take a look at the site and let me know what you think. There are many things that I'd like to do with it, such as surfacing social metrics for the authors, predicting the potential upside for an article based on the historical bit.ly scores of the authors, etc.

If you click through to an article from the site, you will be contributing to its bit.ly score!

A key aspect of this is, of course, that the interrogator is communicating with an equal in terms of the mode, pace and structure of dialogue (it is possible that a computer could succeed at this deception but reveal itself by being implausibly smarter than a human, but that is a question we can enjoy a little later).

As we have since learned, creating AIs is extremely hard and requires a very large portion of the smart people coming out of a broad spectrum of disciplines including software engineering, robotics, psychology, cognitive science and linguistics.

Another enabler is industrial context which brings the pragmatics of real world problems, and the scale and funding that is often not available to academics and if so doesn't benefit from stark focus required to make progress that is provided by industry.

However, we currently have the following:

• Search engines that don't understand language and which attempt to mediate between people (searches by people and documents by people),
• The best and the brightest coming to work for document oriented web companies.

I can't help but wonder where the AI project would be today if web search (as it is currently envisioned) hadn't gobbled up so much bandwidth.

BlogPulse was originally envisioned by Natalie Glance, myself and other colleagues at Intelliseek as a way to track popular blog posts, people and phrases in the blogosphere. It launched with a sparse set of features in 2003 with the following design:

including key phrases which, at that time looked like this:

The site evolved to become a full blog search engine (I was actually against this at the time preferring to focus on analytics) and launched what was my favourite feature in 2004 : trend search. By that time the site was looking far more mature:

In that year, BlogPulse was named a 'trendsetting product' by KMWorld.

On top of the evolving set of capabilities, we started to publish longer analytical articles including this analysis of the Swift Boat story:

And these views of the 2005 Tsunami:

While (I assume) these assets will no longer be available from their adoptive source, the are archived at the wonderful Web Archive, so if you are feeling nostalgic for a simpler, slightly less caffeinated social media world, head on over and take a look.

One final note: I've always felt that social media analysis, just as it gets comfortable with a particular form of content, gets distracted by a new, shiny channel, abandons the legacy data and starts furiously reinventing its wheels. This certainly happened with the blogosphere when Twitter and Facebook showed up and consumers started to believe that 'real time' was something the blogosphere couldn't provide. From where I'm standing, blogs are alive!

If you have any fond memories of BlogPulse, please drop them in the comments to this blog. If you have generated some interesting trend graphs, send me a link and I'll summarize them in an update to this post.

For the record, the number of discovered blogs reported by BlogPulse right now is 182,397,015.

Microsoft:

Google

I can imagine a mashup of this data using eggs and one or more baskets.

As you pan and scroll the map, the image changes tracking these movements.

Bing and Google both present this type of result. If you are a skier, you'll know that before heading out you want to know the condition of the slopes. Searching on Bing for 'snoqualmie' or 'whistler' does just that:

Google doesn't have any answer for skiers as far as I can tell. What I did note though was that if certain snow report websites surface in the results, summar data is extracted:

This is a weaker approach, however, as it relies on the site having the right content and ranking as opposed to Bing strong analysis of intention and curration of appropriate answer data.

Bing, with its rich image and video based home page, gets to show its personality, and these answers shouldn't surprise anyone whose seen today's video:

BTW, there's a line at the end of Gosford Park spoken by the head of the staff which goes something like 'I'm the perfect servant - I know what they want before they know it themselves.'