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Recommendation of hashtags in social Twitter network

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  • King Chau Cheung
  • Tommy King Yin Cheung

Abstract

The development of microblogging services has resulted in the growth of short-text social networking on the internet which open the door to many useful applications such as reputation management and marketing. With more than millions of tweets generated each day, Twitter is one of the largest microblogging sites which allow users to use hashtags to categorise and facilitate the search of tweets which share the same tag. By using a popular or appropriate hashtag in tweets, users could reach a large set of target followers. In this paper, we propose a novel hidden topic model for content-based hashtag recommendation. By ranking the occurrence probability of hashtags of a given topic, a set of hashtag candidates was selected for further analysis. The proposed method is demonstrated with tweets collected from Twitter's API for 19 consecutive periods. The advantage of our model is a combination of the use of topic distribution and term selection probability for hashtag recommendation.

Suggested Citation

  • King Chau Cheung & Tommy King Yin Cheung, 2017. "Recommendation of hashtags in social Twitter network," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 9(3), pages 222-236.
    • Handle: RePEc:ids:injdan:v:9:y:2017:i:3:p:222-236
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    Cited by:

    1. Babak Amiri & Ramin Karimianghadim & Navid Yazdanjue & Liaquat Hossain, 2021. "Research topics and trends of the hashtag recommendation domain," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2689-2735, April.

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