Abstract
Online users are talking across social media sites, on public forums and within customer feedback channels about products, services and their experiences, as well as their likes and dislikes. The continuous monitoring of reviews is ever more important in order to identify leading topics and content categories and to understand how those topics and categories are relevant to customers according to their habits. In this context, the chapter proposes an Opinion Mining model to analyze and summarize reviews related to generic categories of products and services. The process, based on a linguistic approach to the analysis of the opinions expressed, includes the extraction of features terms from the reviews in generic domains. It is also capable to determine the positive or negative valence of the identified features exploiting FreeWordNet, a WordNet-based linguistic resource of adjectives and adverbs involved in the whole process.
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Tuveri, F., Angioni, M. (2014). An Opinion Mining Model for Generic Domains. In: Lai, C., Giuliani, A., Semeraro, G. (eds) Distributed Systems and Applications of Information Filtering and Retrieval. Studies in Computational Intelligence, vol 515. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40621-8_3
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DOI: https://doi.org/10.1007/978-3-642-40621-8_3
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