SMP 2015: Social Media Processing pp 38-50 | Cite as

Personalized Hashtag Suggestion for Microblogs

Conference paper
First Online:
Part of the Communications in Computer and Information Science book series (CCIS, volume 568)

Abstract

In microblogging services, users can generate hashtags to categorize their tweets. However, a majority of microblogs do not contain hashtags, which has intrigued active research on the problem of automatic hashtag recommendation for microblogs. Previous work conducted on this problem mostly does not take the user’s preference into consideration. In this paper, we propose a novel personalized hashtag recommendation method for microblogs based on a probabilistic generative model which exploits users’ perspectives on microblog posts for hashtag generation. Our experiments on a real microblogs dataset show that the proposed method outperforms state-of-the-art methods. We also show some case studies that demonstrate the advantages of considering both the content and user’s personal preferences for hashtag suggestion.

Keywords

Topic Model Latent Dirichlet Allocation Topic Distribution Word Alignment Topic Word 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Copyright information

© Springer Science+Business Media Singapore 2015

Authors and Affiliations

  1. 1.Shanghai Key Laboratory of Intelligent Information Processing, School of Computer ScienceFudan UniversityShanghaiChina

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