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.
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Calvo, H. (2015). Opinion Analysis in Social Networks Using Antonym Concepts on Graphs. In: Dang, T., Wagner, R., Küng, J., Thoai, N., Takizawa, M., Neuhold, E. (eds) Future Data and Security Engineering. FDSE 2015. Lecture Notes in Computer Science(), vol 9446. Springer, Cham. https://doi.org/10.1007/978-3-319-26135-5_9
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DOI: https://doi.org/10.1007/978-3-319-26135-5_9
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