The Study of Developing Korean SentiWordNet for Big Data Analytics : Focusing on Anger Emotion

Sukjae Choi, Ohbyung Kwon

Abstract


Efforts to identify user’s recognition which exists in the big data are being conducted actively. They try to measure scores of people’s view about products, movies and social issues by analyzing statements raised on Internet bulletin boards or SNS. So this study deals with the problem of determining how to find the emotional vocabulary and the degree of these values. The survey methods are using the results of previous studies for the basic emotional vocabulary and degree, and inferring from the dictionary’s glosses for the extended emotional vocabulary. The results were found to have the 4 emotional words lists (vocabularies) as basic emotional list, extended 1 stratum 1 level list from basic vocabulary’s glosses, extended 2 stratum 1 level list from glosses of non-emotional words, and extended 2 stratum 2 level list from glosses’ glosses. And we obtained the emotional degrees by applying the weight of the sentences and the emphasis multiplier values on the basis of basic emotional list. Experimental results have been identified as AND and OR sentence having a weight of average degree of included words. And MULTIPLY sentence having 1.2 to 1.5 weight depending on the type of adverb. It is also assumed that NOT sentence having a certain degree by reducing and reversing the original word’s emotional degree. It is also considered that emphasis multiplier values have 2 for 1 stratum and 3 for 2 stratum.


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References


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