首页    期刊浏览 2024年12月03日 星期二
登录注册

文章基本信息

  • 标题:Hashtag Recommendation Methods for Twitter and Sina Weibo: A Review
  • 本地全文:下载
  • 作者:Areej Alsini ; Du Q. Huynh ; Amitava Datta
  • 期刊名称:Future Internet
  • 电子版ISSN:1999-5903
  • 出版年度:2021
  • 卷号:13
  • 期号:5
  • 页码:129
  • DOI:10.3390/fi13050129
  • 出版社:MDPI Publishing
  • 摘要:Hashtag recommendation suggests hashtags to users while they write microblogs in social media platforms. Although researchers have investigated various methods and factors that affect the performance of hashtag recommendations in Twitter and Sina Weibo, a systematic review of these methods is lacking. The objectives of this study are to present a comprehensive overview of research on hashtag recommendation for tweets and present insights from previous research papers. In this paper, we search for articles related to our research between 2010 and 2020 from CiteSeer, IEEE Xplore, Springer and ACM digital libraries. From the 61 articles included in this study, we notice that most of the research papers were focused on the textual content of tweets instead of other data. Furthermore, collaborative filtering methods are seldom used solely in hashtag recommendation. Taking this perspective, we present a taxonomy of hashtag recommendation based on the research methodologies that have been used. We provide a critical review of each of the classes in the taxonomy. We also discuss the challenges remaining in the field and outline future research directions in this area of study.
  • 关键词:survey; hashtag recommendation; hashtags; Twitter; Sina Weibo survey ; hashtag recommendation ; hashtags ; Twitter ; Sina Weibo
国家哲学社会科学文献中心版权所有