DocumentCode
3158881
Title
Analyzing User Retweet Behavior on Twitter
Author
Zhiheng Xu ; Qing Yang
Author_Institution
Inst. of Autom., Beijing, China
fYear
2012
fDate
26-29 Aug. 2012
Firstpage
46
Lastpage
50
Abstract
This paper provides a deep analysis of user retweet behavior on Twitter. While previous works about analyzing retweet have mainly focused on predicting the retweetability of each tweet, they lacked interpretations at an individual level. In this paper, we perform a general analysis of retweet behavior from the perspective of individual users. Specifically, we train a prediction model to forecast whether a tweet will be retweeted by a given user, leveraging four different types of features: social-based, content-based, tweet-based and author-based features. By performing “leave-one-feature-out” comparisons, we identify factors that are strongly associated with user retweet behavior.
Keywords
behavioural sciences computing; social networking (online); Twitter; author-based feature; content-based feature; prediction model; social-based feature; tweet-based feature; user retweet behavior analysis; Feature extraction; Logistics; Predictive models; Support vector machines; Training; Twitter; Twitter; retweet behavior; social media;
fLanguage
English
Publisher
ieee
Conference_Titel
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location
Istanbul
Print_ISBN
978-1-4673-2497-7
Type
conf
DOI
10.1109/ASONAM.2012.18
Filename
6425786
Link To Document