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Please use this identifier to cite or link to this item: http://hdl.handle.net/UCSP/15849
Title: Dictionary-based sentiment analysis applied to specific domain using a web mining approach
Authors: Cruz Quispe, Laura Vanessa
Ochoa Luna, José Eduardo
Roche, Mathieu
Poncelet, Pascal
Keywords: Data mining;Information management;Natural language processing systems;Websites;Lexical resources;Multiple domains;NAtural language processing;Sentiment analysis;Sentiment dictionaries;SentiWordNet;Social media;Web-mining approach;Big data
Issue Date: 2016
Publisher: CEUR-WS
metadata.dc.relation.uri: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006153487&partnerID=40&md5=41cabb33e2943f3a8d12e6af0668841d
Abstract: In recent years, the Web and social media are growing exponentially. We are provided with documents which have opinions expressed about several topics. This constitute a rich source for Natural Language Processing tasks, in particular, Sentiment Analysis. In this work, we aim at constructing a sentiment dictionary based on words obtained from web pages related to a specific domain. To do so, we correlate candidate opinion words, seed words and domain using AcroDefMI3 and TrueSkill methods. This dictionarybased approach is compared to the SentiWordNet lexical resource. Experimental results show suitability of our approach for multiple domains and infrequent opinion words.
URI: http://repositorio.ucsp.edu.pe/handle/UCSP/15849
ISSN: 16130073
Appears in Collections:Artículos - Ciencia de la computación

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