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dc.contributor.advisor Menczer, Filippo en_US Ratkiewicz, Jacob Paul en_US 2011-10-19T20:17:56Z 2028-06-19T20:17:57Z 2012-03-03T21:45:04Z 2011-10-19T20:17:56Z 2011 en_US
dc.description Thesis (Ph.D.) - Indiana University, Computer Sciences, 2011 en_US
dc.description.abstract 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, which focuses on the case of the deceptive dissemination of ideas, or so-called astroturf. en_US
dc.language.iso en en_US
dc.publisher [Bloomington, Ind.] : Indiana University en_US
dc.rights This work is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0) license.
dc.subject twitter
dc.subject Network growth models en_US
dc.subject Popularity dynamics en_US
dc.subject Network science en_US
dc.subject social systems
dc.subject online systems
dc.subject wikipedia
dc.subject truthy
dc.subject.classification Computer Science en_US
dc.title The Expression of Human Behavior in Online Networks en_US
dc.type Doctoral Dissertation en_US

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