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Information Diffusion in Online Social Network

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Title: Information Diffusion in Online Social Network
Author(s): Lin, Shuyang
Advisor(s): Yu, Philip S.
Contributor(s): Liu, Bing; Ziebart, Brian; Wang, Jing; Zhang, Kunpeng
Department / Program: Computer Science
Graduate Major: Computer Science
Degree Granting Institution: University of Illinois at Chicago
Degree: PhD, Doctor of Philosophy
Genre: Doctoral
Subject(s): information diffusion social influence online social networks
Abstract: Recently, online social networks have become increasingly important media. From online social networks, people get all kinds of information, from popular restaurants in town, to breaking news from the other side of the world. Unlike traditional media that hold a one-to-all communication paradigm, social networks propagate information via word-of-mouth communication between users. The flourishing of social networks as new media have brought numerous applications for the researches on information diffusion. For example, viral marketing campaigns in social networks can benefit from an accurate model of information diffusion. Nevertheless, many research efforts still need to be made to fully understand the diffusion of information in online social networks. In this thesis, we focus on information diffusion in online social networks. We study real-world diffusion data from online social networks such as Twitter, Foursquare, and Slashdot to get data-driven observations. These observations lead us to rethink some key problems with regard to information diffusion: diffusion modeling, trend predicting, and influence maximization.
Issue Date: 2015-10-21
Genre: thesis
URI: http://hdl.handle.net/10027/19656
Rights Information: Copyright 2015 Shuyang Lin
Date Available in INDIGO: 2015-10-21
Date Deposited: 2015-08
 

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