Abstract
Forum has long been the main way of communication, and more and more users publish their opinions by it. The most influential users or opinion leaders will contribute to the formation of information, especially the positive influential users who can guide public opinions and make positive influence. Positive Opinion Leader Group (POLG) represents a group of users, each of who expresses the similar content and same sentiment orientation with their followers to a great extent, who are regarded as the most influential men during the information dissemination process. However, most existing researches pay less attention to the implicit relationship, heterogeneous structure and positive influence. In this paper, we focus on modeling multi-themes user network of forum with explicit and implicit links for this purpose. In detail, we put forward a data structure Longest Sequence Phrase Tree (LSP-Tree) for representing comments on forum, measuring the similarity between comments based on LSP-Tree to obtain implicit links, and further detecting positive opinion leader group. Experiments using dataset from Tianya forum show that our method can detect positive opinion leaders group effectively and efficiently.
Project supported by the State Key Development Program for Basic Research of China (Grant No. 2011CB302200-G), National Natural Science Foundation of China (Grant No. 60973019, 61100026), and the Fundamental Research Funds for the Central Universities(N100704001).
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Song, K., Wang, D., Feng, S., Wang, D., Yu, G. (2012). Detecting Positive Opinion Leader Group from Forum. In: Gao, H., Lim, L., Wang, W., Li, C., Chen, L. (eds) Web-Age Information Management. WAIM 2012. Lecture Notes in Computer Science, vol 7418. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32281-5_10
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DOI: https://doi.org/10.1007/978-3-642-32281-5_10
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