Meme-tracking, Diffusion, and the Flow of On-Line Information

Abstract: News, discussion, and opinions travel through an overlapping set of on-line networks, involving e-mail, blogging, and other forms of communication. We discuss a set of approaches for tracking pieces of text as they travel and mutate in these networks, applying these ideas to a set of related problems. First, we show how this type of analysis can capture temporal patterns in the news over a daily time-scale --- in particular, the succession of story lines that evolve, compete for attention, and collectively produces an effect that commentators refer to as the `news cycle.' Second, we show how this approach can be combined with an analysis of network structure to trace the diffusion of specific pieces of information as they spread between people at a global scale. This talk includes joint work with Lars Backstrom, Jure Leskovec, and David Liben-Nowell.

A tempest: Or, On the flood of interest in sentiment analysis, opinion mining, and the computational treatment of subjective language.

Abstract: "What do other people think?" has always been an important consideration to most of us when making decisions. Long before the World Wide Web, we asked our friends who they were planning to vote for and consulted Consumer Reports to decide which dishwasher to buy. But the Internet has (among other things) made it possible to learn about the opinions and experiences of those in the vast pool of people that are neither our personal acquaintances nor well-known professional critics --- that is, people we have never heard of. Enter sentiment analysis, a flourishing research area devoted to the computational treatment of subjective and opinion-oriented language. Sample phenomena to contend with range from sarcasm in blog postings to the interpretation of political speeches. This talk will cover some of the motivations, challenges, and approaches in this broad and exciting field.