Predicting ReTweet Count Using Visual Cues

被引:44
作者
Can, Ethem F. [1 ]
Oktay, Huseyin [1 ]
Manmatha, R. [1 ]
机构
[1] Univ Massachusetts, Sch Comp Sci, 140 Governors Dr, Amherst, MA 01003 USA
来源
PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13) | 2013年
关键词
Twitter; Retweet prediction; Social Media; Visual Cues;
D O I
10.1145/2505515.2507824
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Social media platforms allow rapid information diffusion, and serve as a source of information to many of the users. Particularly, in Twitter information provided by tweets diffuses over the users through retweets. Hence, being able to predict the retweet count of a given tweet is important for understanding and controlling information diffusion on Twitter. Since the length of a tweet is limited to 140 characters, extracting relevant features to predict the retweet count is a challenging task. However, visual features of images linked in tweets may provide predictive features. In this study, we focus on predicting the expected retweet count of a tweet by using visual cues of an image linked in that tweet in addition to content and structure-based features.
引用
收藏
页码:1481 / 1484
页数:4
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