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http://dx.doi.org/10.7583/JKGS.2017.17.2.135

A Crowdsourcing-based Emotional Words Tagging Game for Building a Polarity Lexicon in Korean  

Kim, Jun-Gi (Graduate School of Culture, Information, and Public Policy (Game Producing Major), Hongik University)
Kang, Shin-Jin (Graduate School of Culture, Information, and Public Policy (Game Producing Major), Hongik University)
Bae, Byung-Chull (Graduate School of Culture, Information, and Public Policy (Game Producing Major), Hongik University)
Publication Information
Journal of Korea Game Society / v.17, no.2, 2017 , pp. 135-144 More about this Journal
Abstract
Sentiment analysis refers to a way of analyzing the writer's subjective opinions or feelings through text. For effective sentiment analysis, it is essential to build emotional word polarity lexicon. This paper introduces a crowdsourcing-based game that we have developed for efficiently building a polarity lexicon in Korean. First, we collected a corpus from the relating Internet communities using a crawler, and we classified them into words using the Twitter POS analyzer. These POS-tagged words are provided as a form of mobile platform based tagging game in which the players voluntarily tagged the polarities of the words, and then the result was collected into the database. So far we have tagged the polarities of about 1200 words. We expect that our research can contribute to the Korean sentiment analysis research especially in the game domain by collecting more emotional word data in the future.
Keywords
Sentiment Analysis; Gamfication;
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Times Cited By KSCI : 1  (Citation Analysis)
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