Journal of Xidian University ›› 2016, Vol. 43 ›› Issue (4): 51-56+62.doi: 10.3969/j.issn.1001-2400.2016.04.010

• Article • Previous Articles     Next Articles

Novel algorithm for predicting personalized retweet behavior

TANG Xing1;QUAN Yining1;SONG Jianfeng1;DENG Kai1;ZHU Hai2;MIAO Qiguang1   

  1. (1. School of Computer Science and Technology, Xidian Univ., Xi'an  710071, China;
    2. School of Computer Science and Technology, Zhoukou Normal Univ., Zhoukou  466001, China)
  • Received:2015-04-20 Online:2016-08-20 Published:2016-10-12

Abstract:

Recently, models for predicting the user retweet behavior are based mainly on the historical retweet data of all users. However, these models are of homogeneity and could not predict a particular user's behavior. To overcome these problems, we propose an algorithm for predicting personalized retweet behavior. Based on crawled Weibo data, we have conducted an analysis and a selection of retweet features. According to the influential theory, we introduce the multi-task learning framework to divide the tasks into common global tasks and many individual tasks. Our massive experiments show that our algorithm is effective in predicting personalized retweet behavior.

Key words: multi-task learning, personalization, retweet behavior, social networks, microblog, data mining