TY - GEN
T1 - Modeling and predicting the re-post behavior in Sina Weibo
AU - Lu, Xinjiang
AU - Yu, Zhiwen
AU - Guo, Bin
AU - Zhou, Xingshe
PY - 2013
Y1 - 2013
N2 - Study of human behavior patterns is of utmost importance to many areas, such as disease spread, resource allocation, and emergency response. Because of its widespread availability and use, online social networks (OSNs) have become an attractive proxy for studying human behaviors. One of the interesting and challenging problems about OSNs is that how much attention of a post from a user can gain? In this paper, we try to tackle this issue by exploring approaches to predict the amount of reposts any given post will obtain in Sina Weibo, a famous microblogging service in China. Specifically, we propose a Reposts Tree based method to model the reposting process in a temporal dynamic manner. Experiments over the real world collected data indicate that our method is effective on repost predicting.
AB - Study of human behavior patterns is of utmost importance to many areas, such as disease spread, resource allocation, and emergency response. Because of its widespread availability and use, online social networks (OSNs) have become an attractive proxy for studying human behaviors. One of the interesting and challenging problems about OSNs is that how much attention of a post from a user can gain? In this paper, we try to tackle this issue by exploring approaches to predict the amount of reposts any given post will obtain in Sina Weibo, a famous microblogging service in China. Specifically, we propose a Reposts Tree based method to model the reposting process in a temporal dynamic manner. Experiments over the real world collected data indicate that our method is effective on repost predicting.
KW - Reposts predicting
KW - Sina weibo
KW - Social media
UR - http://www.scopus.com/inward/record.url?scp=84893512168&partnerID=8YFLogxK
U2 - 10.1109/GreenCom-iThings-CPSCom.2013.166
DO - 10.1109/GreenCom-iThings-CPSCom.2013.166
M3 - 会议稿件
AN - SCOPUS:84893512168
SN - 9780769550466
T3 - Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013
SP - 962
EP - 969
BT - Proceedings - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013
T2 - 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013
Y2 - 20 August 2013 through 23 August 2013
ER -
