Dictionary-based sentiment analysis applied to a specific domain

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Date
2017
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Journal ISSN
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Publisher
Springer Verlag
Abstract
The web and social media have been growing exponentially in recent years. We now have access to documents bearing opinions expressed on a broad range of topics. This constitutes a rich resource for natural language processing tasks, particularly for sentiment analysis. Nevertheless, sentiment analysis is usually difficult because expressed sentiments are usually topic-oriented. In this paper, we propose to automatically construct a sentiment dictionary using relevant terms obtained from web pages for a specific domain. This dictionary is initially built by querying the web with a combination of opinion terms, as well as terms of the domain. In order to select only relevant terms we apply two measures AcroDefMI3 and TrueSkill. Experiments conducted on different domains highlight that our automatic approach performs better for specific cases. © Springer International Publishing AG 2017.
Description
Keywords
Data mining , Information management , Natural language processing systems , Websites , Automatic approaches , Different domains , NAtural language processing , Sentiment analysis , Sentiment dictionaries , Text mining , Topic-oriented , Web Mining , Big data
Citation
URI
https://hdl.handle.net/20.500.12590/15813
Collections
Artículos - Ciencia de la computación