Classification of Emotional Vocabulary Based on Emoticon for Mobile SNS(Social Network Service) Messenger
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Recently, emotional communication has been developed by emoticons that express user emotion in mediated communication through mobile Social Network Service(SNS). As the development of emoticons increases and the usage becomes more popular, there is a growing demand for items that express the emotional expression and desired meaning by the user. And also mis-communication can occur through different interpretation amongst users. Additionally, the meaning interpreted by the users may be different from the designers’ intended emotional expressions. In this study, we propose a model by classifying emotional vocabularies. First, we collected emotional adjectives and extracted the first set of vocabularies with questionnaires, statistical analysis and FGI (Focus Group Interview). Second, we extracted the final set of proper vocabulary from the first set of vocabularies with a second set of questionnaires and statistical analysis. Third, with the final set of vocabularies an emotional vocabulary model was built based on the multidimensional scale analysis. As a result, the model was classified into 13 categories, which are as follows: sorry, busy, hungry, difficult, sad, the weather is cold or hot, boring, ashamed, curious, satisfy, good, beautiful, and comfortable.
Abstract
Recently, emotional communication has been developed by emoticons that express user emotion in mediated communication through mobile Social Network Service(SNS). As the development of emoticons increases and the usage becomes more popular, there is a growing demand for items that express the emotional expression and desired meaning by the user. And also mis-communication can occur through different interpretation amongst users. Additionally, the meaning interpreted by the users may be different from the designers’ intended emotional expressions. In this study, we propose a model by classifying emotional vocabularies. First, we collected emotional adjectives and extracted the first set of vocabularies with questionnaires, statistical analysis and FGI (Focus Group Interview). Second, we extracted the final set of proper vocabulary from the first set of vocabularies with a second set of questionnaires and statistical analysis. Third, with the final set of vocabularies an emotional vocabulary model was built based on the multidimensional scale analysis. As a result, the model was classified into 13 categories, which are as follows: sorry, busy, hungry, difficult, sad, the weather is cold or hot, boring, ashamed, curious, satisfy, good, beautiful, and comfortable.
참고문헌 (12)
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