TY - GEN
T1 - Tree-based mining for discovering patterns of reposting behavior in microblog
AU - He, Huilei
AU - Yu, Zhiwen
AU - Guo, Bin
AU - Lu, Xinjiang
AU - Tian, Jilei
PY - 2013
Y1 - 2013
N2 - Discovering behavior patterns is important in online human interaction understanding (e.g., how information is shared through reposting, what roles do people play in a conversation). As reposting has become the key mechanism for information propagation in social media (e.g. microblog) and contributes a lot to users' participation in online events, it is important to explore how repost works. Different from previous studies, we make two contributions in this work: firstly, we analyze the patterns of reposting behavior from the perspective of microblog user and employ a special mining method which successfully find interesting results; secondly, our analysis is based on the Sina Weibo, which has different characteristics with Twitter. Specifically, information flow for a certain message in Weibo is represented as a tree. Tree-based pattern mining algorithm is presented to extract a number of interesting patterns which are useful for understanding information diffusion in the Weibo network.
AB - Discovering behavior patterns is important in online human interaction understanding (e.g., how information is shared through reposting, what roles do people play in a conversation). As reposting has become the key mechanism for information propagation in social media (e.g. microblog) and contributes a lot to users' participation in online events, it is important to explore how repost works. Different from previous studies, we make two contributions in this work: firstly, we analyze the patterns of reposting behavior from the perspective of microblog user and employ a special mining method which successfully find interesting results; secondly, our analysis is based on the Sina Weibo, which has different characteristics with Twitter. Specifically, information flow for a certain message in Weibo is represented as a tree. Tree-based pattern mining algorithm is presented to extract a number of interesting patterns which are useful for understanding information diffusion in the Weibo network.
KW - Information propagation
KW - Microblog
KW - Reposting behavior
KW - Tree-based pattern mining
UR - http://www.scopus.com/inward/record.url?scp=84893076585&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-53914-5_32
DO - 10.1007/978-3-642-53914-5_32
M3 - 会议稿件
AN - SCOPUS:84893076585
SN - 9783642539138
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 372
EP - 384
BT - Advanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings
T2 - 9th International Conference on Advanced Data Mining and Applications, ADMA 2013
Y2 - 14 December 2013 through 16 December 2013
ER -