首页    期刊浏览 2024年11月07日 星期四
登录注册

文章基本信息

  • 标题:Predicting the Lifespan and Retweet Times of Tweets Based on Multiple Feature Analysis
  • 本地全文:下载
  • 作者:Bae, Yongjin ; Ryu, Pum-Mo ; Kim, Hyunki
  • 期刊名称:ETRI Journal
  • 印刷版ISSN:1225-6463
  • 电子版ISSN:2233-7326
  • 出版年度:2014
  • 卷号:36
  • 期号:3
  • 页码:418-428
  • DOI:10.4218/etrij.14.0113.0657
  • 语种:English
  • 出版社:Electronics and Telecommunications Research Institute
  • 摘要:In social network services, such as Facebook, Google+, Twitter, and certain postings attract more people than others. In this paper, we propose a novel method for predicting the lifespan and retweet times of tweets, the latter being a proxy for measuring the popularity of a tweet. We extract information from retweet graphs, such as posting times; and social, local, and content features, so as to construct prediction knowledge bases. Tweets with a similar topic, retweet pattern, and properties are sequentially extracted from the knowledge base and then used to make a prediction. To evaluate the performance of our model, we collected tweets on Twitter from June 2012 to October 2012. We compared our model with conventional models according to the prediction goal. For the lifespan prediction of a tweet, our model can reduce the time tolerance of a tweet lifespan by about four hours, compared with conventional models. In terms of prediction of the retweet times, our model achieved a significantly outstanding precision of about 50%, which is much higher than two of the conventional models showing a precision of around 30% and 20%, respectively.
  • 关键词:Tweet;lifespan;retweet;popularity;prediction;social network
国家哲学社会科学文献中心版权所有