Posting topics ≠ reading topics: On discovering posting and reading topics in social media

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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.

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APA

Gong, W., Lim, E. P., & Zhu, F. (2016). Posting topics ≠ reading topics: On discovering posting and reading topics in social media. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9564, pp. 14–28). Springer Verlag. https://doi.org/10.1007/978-3-319-28361-6_2

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