Publication Type

Conference Proceeding Article

Publication Date

1-2016

Abstract

Social media users make decisions about what content to post and read. As posted content is often visible to others, users are likely to impose self-censorship when deciding what content to post. On the other hand, such a concern may not apply to reading social media content. As a result, the topics of content that a user posted and read can be different and this has major implications to the applications that require personalization. To better determine and profile social media users’ topic interests, we conduct a user survey in Twitter. In this survey, participants chose the topics they like to post (posting topics) and the topics they like to read (reading topics). We observe that users’ posting topics differ from their reading topics significantly. We find that some topics such as “Religion”, “Business” and “Politics” attract much more users to read than to post. With the ground truth data obtained from the survey, we further explore the discovery of users’ posting and reading topics separately using features derived from their posted content, received content and social networks.

Discipline

Databases and Information Systems | Social Media

Research Areas

Data Management and Analytics

Publication

Advances in Network Science: 12th International Conference and School, NetSci-X 2016, Wroclaw, Poland, January 11-13, 2016, Proceedings

Volume

9564

First Page

14

Last Page

18

ISBN

9783319283609

Identifier

10.1007/978-3-319-28361-6_2

Publisher

Springer Verlag

City or Country

Cham

Copyright Owner and License

LARC

Additional URL

http://dx.doi.org/10.1007/978-3-319-28361-6_2

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