Abstract
Online comments are ubiquitous in social media such as micro-blogs, forums and blogs. They provide opinions of reviewers that are useful for understanding social media. Identifying opinion leaders from all reviewers is one of the most important tasks to analysis online comments. Most existing methods to identify opinion leaders only consider positive opinions. Few studies investigate the effect of negative opinions on opinion leader identification. In this paper, we propose a novel method to identify opinion leaders from online comments based on both positive and negative opinions. In this method, we first construct a signed network from online comments, and then design a new model based on PageTrust, called TrustRank, to identify opinion leaders from the signed network. Experimental results on the online comments of a real forum show that the proposed method is competitive with other related state-of-the-art methods.
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Chen, Y. et al. (2014). Identifying Opinion Leaders from Online Comments. In: Huang, H., Liu, T., Zhang, HP., Tang, J. (eds) Social Media Processing. SMP 2014. Communications in Computer and Information Science, vol 489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45558-6_21
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DOI: https://doi.org/10.1007/978-3-662-45558-6_21
Publisher Name: Springer, Berlin, Heidelberg
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