Paper Info
Title
We know what @you #tag: does the dual role affect hashtag adoption?
Abstract
Researchers and social observers have both believed that hashtags, as a new type of organizational objects of information, play a dual role in online microblogging communities (e.g., Twitter). On one hand, a hashtag serves as a bookmark of content, which links tweets with similar topics; on the other hand, a hashtag serves as the symbol of a community membership, which bridges a virtual community of users. Are the real users aware of this dual role of hashtags? Is the dual role affecting their behavior of adopting a hashtag? Is hashtag adoption predictable? We take the initiative to investigate and quantify the effects of the dual role on hashtag adoption. We propose comprehensive measures to quantify the major factors of how a user selects content tags as well as joins communities. Experiments using large scale Twitter datasets prove the effectiveness of the dual role, where both the content measures and the community measures significantly correlate to hashtag adoption on Twitter. With these measures as features, a machine learning model can effectively predict the future adoption of hashtags that a user has never used before.
Year
DOI
Venue
2012
10.1145/2187836.2187872
WWW
Keywords
Field
DocType
content measure,real user,community membership,future adoption,hashtag adoption,content tag,virtual community,dual role,large scale twitter datasets,online microblogging community,machine learning,prediction
Joins,World Wide Web,Social media,Computer science,Symbol,Microblogging,Virtual community
Conference
Citations 
PageRank 
References 
88
3.22
23
Authors
4
Name
Order
Citations
PageRank
Lei Yang1883.22
Tao Sun216816.47
Ming Zhang31963107.42
Qiaozhu Mei44395207.09