Category Archives: aggregation

Wikileaks and Collaborative Sensemaking?

Thanks to the head start of the likes of the New York Times, the Guardian, and der Spiegel we now have some excellent written reporting on a few of the more important issues exposed in the wikileaks cablegate data. There have also been a number of visualizations of the dataset published in the last few days (e.g. Infothetics has a niceĀ round-up), which help, to some extent, in browsing and making sense of all of the data there.

But what I want to suggest here is that, with all of the attention that this story is getting, that there may be some useful information to mine from social media about what is interesting, important, and noteworthy in the dataset. One of the most useful aspects of social media such as Twitter is that it provides a platform where interested individuals can make observations about what’s going on around them, including observations of large collections of documents.

At Rutgers, where I work, we’ve been developing a social media visual analytics tool call Vox Civitas and have collected a dataset of almost 60,000 (and growing) English language tweets marked with the hashtag “#cablegate” from Twapperkeeper. Vox provides the ability to visualize the collection over time, with sentiment, and includes capabilities for filtering according to many criteria. Without further ado, click here to see the cablegate dataset in Vox. Let us know what you find or if it inspires any follow-up work!

Truth Markets?

I recently saw this post on the NYTimes which mentions the concept of truth markets, a variant of prediction markets. Prediction markets have been recognized by many as a way to aggregate independent information from lots of individuals and provide a signal (a price) which reflects the aggregate response. Prediction markets have been successfully applied in politics, for instance, the Iowa Electronic Markets, which lets people trade on the what they think the outcome of the next presidential election will be. Truth markets applies the concept to predicting the truth value of a claim or the trustworthiness of a claimant. I don’t know enough about economics but my intuition is that a market approach toward predicting truth would require A LOT or participation to be meaningful in any way. Indeed, a re-reading of Cass Sunstein’s Infotopia lays out some of the limitations of prediction markets: knowledge needs to be dispersed (not concentrated), a wide range of people need to have relevant facts, and people need to be able to be incentivized to reveal their information through investment.

Furthermore there’s the issue that markets aggregate information not only about facts but also about tastes. Investment markets ostensibly do not do this because the assumption is that people invest not based on their own tastes but on their desire to earn money. But in some sense, I might invest because I predict that some good is going to be popular or appeal to mass taste, and thus earn money on my investment. So in a sense, you would be aggregating predictions about what people think about other people’s tastes (including how your own factors in to that). This would only hold for a mass market good; other investments may not be susceptible to this in the same way. In terms of the application of these ideas to truth markets, the point is that there is a component to prediction markets that are based on predictions of mass taste and there is a component that is based on objective fact; the key would be to realy mitigate any subjective (taste based) component of the market so that objective facts can rule the market. This is a tall order.