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Opinion Analysis in Social Networks Using Antonym Concepts on Graphs

  • Hiram CalvoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9446)

Abstract

In sentiment analysis a text is usually classified as positive, negative or neutral; in this work we propose a method for obtaining the relatedness or similarity that an opinion about a particular subject has with regard to a pair of antonym concepts. In this way, a particular opinion is analyzed in terms of a set of features that can vary depending on the field of interest. With our method, it is possible, for example, to determine the balance of honesty, cleanliness, interestingness, or expensiveness that is expressed in an opinion. We used the standard similarity measures Hirst-St-Onge, Jiang-Conrath and Resnik from WordNet; however, finding that these measures are not well-suitable for working with all Parts-of-Speech, we additionally proposed a new measure based on graphs, to properly handle adjectives. We validated our results with a survey to a sample of 20 individuals, obtaining a precision above 82 % with our method.

Keywords

Sentiment analysis Opinion mining Adjective similarity measure Wordnet Antonyms 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Centro de Investigación en Computación, Instituto Politécnico Nacional, Center for Computing ResearchNational Polytechnic InstituteVallejoMexico

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