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Title:How others affect your Twitter #hashtag adoption? Examination of community-based and context-based information diffusion in Twitter
Author(s):Zhang, Chenwei; Gao, Zheng; Liu, Xiaozhong
Subject(s):information diffusion
graph mining
community detection
context based similarity
Abstract:Twitter has become a rich source of people’s opinions about a variety of topics, such as their daily life, and current news. Twitter’s retweeting and mentioning mechanisms enable users to disseminate information broadly. In this study, we investigate the effects of community-based and context-based features on the users’ information adoption and diffusion patterns in Twitter. Community-based features capture how the adoption of a hashtag by users within the target user’s community and users outside that community influences the target user’s selection of the target hashtag. Context-based features measure the influence of other users’ adoption of hashtags that are semantically similar with a hashtag on the target user’s adoption of this hashtag. We find the community-based features enhance the prediction of users’ hashtag adoption and diffusion. However, the further exploration of context-based features is needed.
Issue Date:2016-03-15
Publisher:iSchools
Citation Info:NA
Series/Report:IConference 2016 Proceedings
Genre:Conference Poster
Type:Text
Language:English
URI:http://hdl.handle.net/2142/89425
DOI:10.9776/16538
Rights Information:Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.
Date Available in IDEALS:2016-03-08


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