Paper: Collective Opinion Target Extraction in Chinese Microblogs

ACL ID D13-1189
Title Collective Opinion Target Extraction in Chinese Microblogs
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013

Microblog messages pose severe challenges for current sentiment analysis techniques due to some inherent characteristics such as the length limit and informal writing style. In this paper, we study the problem of extracting opinion targets of Chinese microblog messag- es. Such fine-grained word-level task has not been well investigated in microblogs yet. We propose an unsupervised label propagation al- gorithm to address the problem. The opinion targets of all messages in a topic are collec- tively extracted based on the assumption that similar messages may focus on similar opinion targets. Topics in microblogs are identified by hashtags or using clustering algorithms. Ex- perimental results on Chinese microblogs show the effectiveness of our framework and algorithms.