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.
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Xu, J., Zhang, Q., Huang, X. (2015). Personalized Hashtag Suggestion for Microblogs. In: Zhang, X., Sun, M., Wang, Z., Huang, X. (eds) Social Media Processing. SMP 2015. Communications in Computer and Information Science, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-0080-5_4
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DOI: https://doi.org/10.1007/978-981-10-0080-5_4
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