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Characterizing Online Social Media: Topic Inference and Information Propagation

Word-of-mouth (WOM) communication is a well studied phenomenon in the literature and content propagation in Online Social Networks (OSNs) is one of the forms of WOM mechanism that have been prevalent in recent years specially with the widespread surge of online communities and online social networks. The basic piece of information in most OSNs is a post (e.g., a tweet in Twitter or a post in Facebook). A post can contain different types of content such as text, photo, video, etc, or a mixture of two or more them. There are also various ways to enrich the text by mentioning other users, using hashtags, and adding URLs to external contents. The goal of this study is to investigate what factors contribute into the propagation of messages in Google+. To answer to this question a multidimensional study will be conducted. On one hand this question could be viewed as a natural language processing problem where topic or sentiment of posts cause message dissemination. On the other hand the propagation can be effect of graph properties i.e., popularity of message originators (node degree) or activities of communities. Other aspects of this problem are time, external contents, and external events. All of these factors are studied carefully to find the most highly correlated attribute(s) in the propagation of posts.

Identiferoai:union.ndltd.org:uoregon.edu/oai:scholarsbank.uoregon.edu:1794/23904
Date31 October 2018
CreatorsRezayidemne, Seyedsaed
ContributorsRejaie, Reza
PublisherUniversity of Oregon
Source SetsUniversity of Oregon
Languageen_US
Detected LanguageEnglish
TypeElectronic Thesis or Dissertation
RightsAll Rights Reserved.

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