TY - GEN
T1 - Understanding Sina Weibo online social network
T2 - 2013 IEEE Global Communications Conference, GLOBECOM 2013
AU - Lei, Kai
AU - Zhang, Kai
AU - Xu, Kuai
PY - 2013
Y1 - 2013
N2 - Sina Weibo, one of the most popular online social networks in China, has recently become a critical medium for Internet users to disseminate and discuss breaking news, social events and other information. Although online social networks and social media have received significant attention from the research community, few studies have focused on Sina Weibo due to the lack of data collection. Given the sheer size of Sina Weibo online social network and vast amount of tweets, retweets and comments, this paper introduces a novel community approach for understanding Sina Weibo online social network. Specifically, we collect all Weibo users registered with Shenzhen as primary geographic location, and build a Shenzhen Weibo community graph based on their following or follower relationships. Our experimental results describe interesting graphical characteristics such as clustering coefficients of this community graph, and reveal the impact of user popularity on tweet influence. Through modeling interactions of Shenzhen Weibo users and their tweeted messages with bipartite graphs and one-mode projections, we analyze the similarity of retweeting and commenting activities among these users, and discuss the implications of the findings on understanding different types of user accounts and the motivations of their following and retweeting behaviors. To the best of our knowledge, this study is the first effort to introduce a community approach for understanding the community characteristics of Sina Weibo and characterizing the similarity of retweeting behaviors and following relationships.
AB - Sina Weibo, one of the most popular online social networks in China, has recently become a critical medium for Internet users to disseminate and discuss breaking news, social events and other information. Although online social networks and social media have received significant attention from the research community, few studies have focused on Sina Weibo due to the lack of data collection. Given the sheer size of Sina Weibo online social network and vast amount of tweets, retweets and comments, this paper introduces a novel community approach for understanding Sina Weibo online social network. Specifically, we collect all Weibo users registered with Shenzhen as primary geographic location, and build a Shenzhen Weibo community graph based on their following or follower relationships. Our experimental results describe interesting graphical characteristics such as clustering coefficients of this community graph, and reveal the impact of user popularity on tweet influence. Through modeling interactions of Shenzhen Weibo users and their tweeted messages with bipartite graphs and one-mode projections, we analyze the similarity of retweeting and commenting activities among these users, and discuss the implications of the findings on understanding different types of user accounts and the motivations of their following and retweeting behaviors. To the best of our knowledge, this study is the first effort to introduce a community approach for understanding the community characteristics of Sina Weibo and characterizing the similarity of retweeting behaviors and following relationships.
UR - http://www.scopus.com/inward/record.url?scp=84904119374&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84904119374&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2013.6831550
DO - 10.1109/GLOCOM.2013.6831550
M3 - Conference contribution
AN - SCOPUS:84904119374
SN - 9781479913534
SN - 9781479913534
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 3114
EP - 3119
BT - 2013 IEEE Global Communications Conference, GLOBECOM 2013
Y2 - 9 December 2013 through 13 December 2013
ER -