The expression of human behavior in online networks
The wide adoption of Web 2.0, in which users can interact with Web sites to generate new content, has a serendipitous side effect. All of this user-generated data provides researchers with a unique lens on the behavior of the users who created it. While instrumenting millions of users with a device that records everything they read in real life would be impossible, we can easily record the articles they read on Wikipedia. Similarly, we can use Twitter data to map the interactions between tens of thousands of people, as well as studying the topics they discuss.
I outline several studies taking advantage of this trove of behavioral data. Initially focusing on Wikipedia, I examine the patterns in the paths that users take when navigating from article to article, and contrast these with similar data for several other large Internet destinations. I then develop an understanding of bursty popularity dynamics, discovering that bursts in the attention to a page have dynamics similar to that observed in natural phenomena, like earthquakes and avalanches; I also present a simple model able to capture these dynamics. Next I switch gears—away from looking at users as they travel between topics, and towards looking at how topics (memes) travel between users, and how users interact with each other. I frame this research in the context of political discussion on Twitter. I first perform a general overview of the space of this discussion, examining how users connect with each other. I conclude with a case study, the Web site truthy.indiana.edu, which focuses on the case of the deceptive dissemination of ideas, or so-called astroturf.
0984: Computer science