• Cross-Cultural Studies
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• v.45
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• pp.219-243
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• 2016

The life of Antonin Artaud exactly reproduces a very cruel drama. He lived in constant anguish and suffered from severe mental pain. This research will trace his thoughts in his writings while he was a prisoner of language. Artaud was a poet filled with anxiety about language, things, being, and thought. Whenever he tried to explain the mystery of being by means of mundane language, he experienced psychological agony. His poetic thoughts began to break down, because of his identity loss. Nevertheless, he was destined to grasp the world through language. Artaud had suffered from mental illness during his youth. His mental illness was associated with his difficulty in creating poetry. In this research, the letter, Correspondance avec Jacques $Rivi{\grave{e}}re$, is analyzed. The poet refers to "the collapse of the spirit's core, and the erosion of the fundamental thought that slips away" to convey his linguistic incompetence. Hereafter, he constantly demonstrated anxious mental symptoms. Even though he became mentally deranged, he maintained his consciousness, as is apparent in his writings. Also, his spiritual belief is reflected in his mental uneasiness. While he was traveling through the Tarahumaras area in Mexico, he was obsessed with its primitive belief in the Peyote rituals, and he immersed himself in performing them. His unchristian belief was the product of his mystical personality. Until his last breath, he did not give up writing. Artaud's mental derangement does not mean lunacy, but if one insists in calling it so, that is a metaphor. His derangement comes from his refusal to accept his limitations and from his aspiring to regard his body in the same light as his intellectual perceptions. His intellect could manifest more easily when his mind was elevated to the extreme. Artaud's lunacy is no different from that of a profound philosopher. The lives of poets who suffer from mental derangement are more poetic than the lives of those who do not. Artaud's atypical emotions provide a way of to measure our own limitations, helplessness, and resignation. His scream is nonsegmental but different from that of a mental patient. That difference is why people are interested in his works and wish to delve into his writings.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.227-252
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• 2018

The evolution of instant communication has mirrored the development of the Internet and messenger applications are among the most representative manifestations of instant communication technologies. In messenger applications, senders use emoticons to supplement the emotions conveyed in the text of their messages. The fact that communication via messenger applications is not face-to-face makes it difficult for senders to communicate their emotions to message recipients. Emoticons have long been used as symbols that indicate the moods of speakers. However, at present, emoticon-use is evolving into a means of conveying the psychological states of consumers who want to express individual characteristics and personality quirks while communicating their emotions to others. The fact that companies like KakaoTalk, Line, Apple, etc. have begun conducting emoticon business and sales of related content are expected to gradually increase testifies to the significance of this phenomenon. Nevertheless, despite the development of emoticons themselves and the growth of the emoticon market, no suitable emoticon recommendation system has yet been developed. Even KakaoTalk, a messenger application that commands more than 90% of domestic market share in South Korea, just grouped in to popularity, most recent, or brief category. This means consumers face the inconvenience of constantly scrolling around to locate the emoticons they want. The creation of an emoticon recommendation system would improve consumer convenience and satisfaction and increase the sales revenue of companies the sell emoticons. To recommend appropriate emoticons, it is necessary to quantify the emotions that the consumer sees and emotions. Such quantification will enable us to analyze the characteristics and emotions felt by consumers who used similar emoticons, which, in turn, will facilitate our emoticon recommendations for consumers. One way to quantify emoticons use is metadata-ization. Metadata-ization is a means of structuring or organizing unstructured and semi-structured data to extract meaning. By structuring unstructured emoticon data through metadata-ization, we can easily classify emoticons based on the emotions consumers want to express. To determine emoticons' precise emotions, we had to consider sub-detail expressions-not only the seven common emotional adjectives but also the metaphorical expressions that appear only in South Korean proved by previous studies related to emotion focusing on the emoticon's characteristics. We therefore collected the sub-detail expressions of emotion based on the "Shape", "Color" and "Adumbration". Moreover, to design a highly accurate recommendation system, we considered both emotion-technical indexes and emoticon-emotional indexes. We then identified 14 features of emoticon-technical indexes and selected 36 emotional adjectives. The 36 emotional adjectives consisted of contrasting adjectives, which we reduced to 18, and we measured the 18 emotional adjectives using 40 emoticon sets randomly selected from the top-ranked emoticons in the KakaoTalk shop. We surveyed 277 consumers in their mid-twenties who had experience purchasing emoticons; we recruited them online and asked them to evaluate five different emoticon sets. After data acquisition, we conducted a factor analysis of emoticon-emotional factors. We extracted four factors that we named "Comic", Softness", "Modernity" and "Transparency". We analyzed both the relationship between indexes and consumer attitude and the relationship between emoticon-technical indexes and emoticon-emotional factors. Through this process, we confirmed that the emoticon-technical indexes did not directly affect consumer attitudes but had a mediating effect on consumer attitudes through emoticon-emotional factors. The results of the analysis revealed the mechanism consumers use to evaluate emoticons; the results also showed that consumers' emoticon-technical indexes affected emoticon-emotional factors and that the emoticon-emotional factors affected consumer satisfaction. We therefore designed the emoticon recommendation system using only four emoticon-emotional factors; we created a recommendation method to calculate the Euclidean distance from each factors' emotion. In an attempt to increase the accuracy of the emoticon recommendation system, we compared the emotional patterns of selected emoticons with the recommended emoticons. The emotional patterns corresponded in principle. We verified the emoticon recommendation system by testing prediction accuracy; the predictions were 81.02% accurate in the first result, 76.64% accurate in the second, and 81.63% accurate in the third. This study developed a methodology that can be used in various fields academically and practically. We expect that the novel emoticon recommendation system we designed will increase emoticon sales for companies who conduct business in this domain and make consumer experiences more convenient. In addition, this study served as an important first step in the development of an intelligent emoticon recommendation system. The emotional factors proposed in this study could be collected in an emotional library that could serve as an emotion index for evaluation when new emoticons are released. Moreover, by combining the accumulated emotional library with company sales data, sales information, and consumer data, companies could develop hybrid recommendation systems that would bolster convenience for consumers and serve as intellectual assets that companies could strategically deploy.