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http://dx.doi.org/10.13088/jiis.2016.22.3.001

WellnessWordNet: A Word Net for Unconstrained Subjective Well-Being Monitor ing Based on Unstructured Data and Contextual Polarity  

Song, Yeongeun (School of Management, Kyung Hee University)
Nam, Suhyun (School of Management, Kyung Hee University)
Kwon, Ohbyung (School of Management, Kyung Hee University)
Publication Information
Journal of Intelligence and Information Systems / v.22, no.3, 2016 , pp. 1-21 More about this Journal
Abstract
IT-based subjective well-being (SWB) services, a main part of wellness IT, should measure the SWB state of individuals in an unrestrained, cost-effective manner. The dictionaries for sentiment analysis available in the market may be useful for this purpose, but obtaining proper sentiment values using only words from the sentiment lexicon is impossible; therefore, a new dictionary including wellness vocabulary is needed. The existing sentiment dictionaries link only a single sentiment value to a single sentiment word, although sentiment values may vary depending on personal traits. In this study, we develop an extended version of the SenticNet sentiment dictionary dubbed WellnessWordNet. SenticNet is considered the best and most expressive among the already existing sentiment dictionaries. Using the information provided by SenticNet, we created a database including the wellness states (estimated values) of stress, depression, and anger to develop the WellnessWordNet system. The accuracy of the system was validated through actual tests with live subjects. This study is unique and unprecedented in that i) an extended sentiment dictionary, WellnessWordNet, is developed; ii) values for wellness state language are offered; and iii) different sentiment values, namely contextual polarity, for people of the same gender or age group are suggested.
Keywords
Subjective Well-Being; Sentiment Analysis; Contextual Polarity; Unstructured Data; SenticNet;
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