How others affect your Twitter #hashtag adoption? Examination of community-based and context-based information diffusion in Twitter

Zhang, Chenwei; Gao, Zheng; Liu, Xiaozhong

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https://hdl.handle.net/2142/89425 Copy

Description

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

Issue Date

2016-03-15

Keyword(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.

Publisher

iSchools

Series/Report Name or Number

IConference 2016 Proceedings

Type of Resource

text

Language

eng

Permalink

http://hdl.handle.net/2142/89425

DOI

https://doi.org/10.9776/16538

Copyright and License Information

Copyright 2016 is held by the authors. Copyright permissions, when appropriate, must be obtained directly from the authors.

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