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      A lexicon based method to search for extreme opinions

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      PLoS ONE
      Public Library of Science

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          Abstract

          Studies in sentiment analysis and opinion mining have been focused on many aspects related to opinions, namely polarity classification by making use of positive, negative or neutral values. However, most studies have overlooked the identification of extreme opinions (most negative and most positive opinions) in spite of their vast significance in many applications. We use an unsupervised approach to search for extreme opinions, which is based on the automatic construction of a new lexicon containing the most negative and most positive words.

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          Lexicon-Based Methods for Sentiment Analysis

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            Affective Computing and Sentiment Analysis

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              Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: Project administrationRole: ResourcesRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                2018
                25 May 2018
                : 13
                : 5
                : e0197816
                Affiliations
                [001] Centro Singular de Investigación en Tecnoloxías da Información (CITIUS), University of Santiago de Compostela, Santiago de Compustela, A Coruña, Spain
                Nanyang Technological University, SINGAPORE
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6970-4888
                Article
                PONE-D-17-27406
                10.1371/journal.pone.0197816
                5969751
                29799867
                f332cd4d-baf0-42de-90d8-bfbe7f5104ac
                © 2018 Almatarneh, Gamallo

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 21 July 2017
                : 28 March 2018
                Page count
                Figures: 5, Tables: 10, Pages: 19
                Funding
                The authors received no specific funding for this work.
                Categories
                Research Article
                Social Sciences
                Linguistics
                Lexicons
                Social Sciences
                Linguistics
                Semantics
                Engineering and Technology
                Electronics
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Machine Learning Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Machine Learning Algorithms
                Computer and Information Sciences
                Artificial Intelligence
                Machine Learning
                Machine Learning Algorithms
                Computer and Information Sciences
                Artificial Intelligence
                Machine Learning
                Physical Sciences
                Mathematics
                Applied Mathematics
                Algorithms
                Research and Analysis Methods
                Simulation and Modeling
                Algorithms
                Social Sciences
                Sociology
                Communications
                Social Communication
                Social Media
                Computer and Information Sciences
                Network Analysis
                Social Networks
                Social Media
                Social Sciences
                Sociology
                Social Networks
                Social Media
                Research and Analysis Methods
                Database and Informatics Methods
                Information Retrieval
                Custom metadata
                The data collected from websites are publicly available data, and no personally identifiable information of the users was gathered, and we complied with all the terms and conditions of service of the websites that we used in this study. - VERY-NEG and VERY-POS lexicons are available from a public githup repository: https://github.com/almatarneh/LEXICONS - Our proposed lexicons were built from the text corpora It is freely available at: https://web.stanford.edu/~cgpotts/data/wordnetscales/wn-asr-multicorpus.csv.zip - 4 types of products (domains): Kitchen, Books, DVDs, and Electronics. It is publicly available at: https://www.cs.jhu.edu/~mdredze/datasets/sentiment/domain_sentiment_data.tar.gz - Movie Review Dataset: http://ai.stanford.edu/~amaas/data/sentiment/.

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