TY - GEN
T1 - Deriving marketing intelligence over microblogs
AU - Li, Yung-Ming
AU - Li, Tsung Ying
PY - 2011/3/28
Y1 - 2011/3/28
N2 - With rapid growing popularity, microblogs have become a great source of consumer opinions. Confronting unique properties and massive volume of posts on microblogs, this paper proposes a summarization framework that provides compact numeric summarization for microblogs opinions. The proposed framework is designed to cope with four major tasks: 1) topics detection, 2) sentiment classification, 3) credibility assessment and 4) score aggregation. The experiment is held on twitter, the largest microblog platform, for proving the efficiency and correctness of the framework. We found the consideration of user credibility and opinion quality is essential for aggregating microblog opinions.
AB - With rapid growing popularity, microblogs have become a great source of consumer opinions. Confronting unique properties and massive volume of posts on microblogs, this paper proposes a summarization framework that provides compact numeric summarization for microblogs opinions. The proposed framework is designed to cope with four major tasks: 1) topics detection, 2) sentiment classification, 3) credibility assessment and 4) score aggregation. The experiment is held on twitter, the largest microblog platform, for proving the efficiency and correctness of the framework. We found the consideration of user credibility and opinion quality is essential for aggregating microblog opinions.
UR - http://www.scopus.com/inward/record.url?scp=79952943405&partnerID=8YFLogxK
U2 - 10.1109/HICSS.2011.143
DO - 10.1109/HICSS.2011.143
M3 - Conference contribution
AN - SCOPUS:79952943405
SN - 9780769542829
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
BT - Proceedings of the 44th Annual Hawaii International Conference on System Sciences, HICSS-44 2010
T2 - 44th Hawaii International Conference on System Sciences, HICSS-44 2010
Y2 - 4 January 2011 through 7 January 2011
ER -