• Cross-Cultural Studies
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• v.41
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• pp.33-56
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• 2015

Trauma studies have provided useful models for dealing with the catastrophic and disastrous events that an individual and collective group experience. Most important of all, the perspective of post-structuralist trauma study, including Cathy Caruth, became a paradigmatic model and it has been applied to almost all contexts of life. The perspective of this study model, which is called an "event-based model of trauma," focuses on the literal registration of the traumatic event and the accurate and immediate recall of the past. The person directly involved in the event becomes the passive bearer transmitting the truth of a traumatic event. From this perspective, the traumatic subject only undergoes and endures the event and cannot play an active role in constructing trauma and dealing with it. Eventually, the truth of trauma has to be obtained at the cost of the traumatic subject's autonomy and the possibility of his/her agency. The problem here is that the truth, which is reencountered through the literal return of the past, obtained at the cost of the subject's autonomy, strikes a rather fatal blow to the person, than gives help for resolving many of matters surrounding traumatic experience and curing trauma. This suggests that the active way of dealing with trauma on the part of the traumatic subject, rather than the traumatic event itself, is demanded. Furthermore, because more recently, images of disastrous events were viewed "live" by audiences and an immediacy to the event is replicated in public discourse about them, the event becomes more immediately traumatic and there is a more strong presumption that people regard themselves as traumatic victims than before. This is the reason that we must explore an active way dealing with trauma on more human position at this time. This essay aims to examine the limits of the paradigmatic model of trauma study, an "event-based model of trauma," critically through a literary, theoretical text in which it reveals how the literal return of the traumatic past have a fatal effect on the victim; and hopes to suggest "the narrative memory" as a way to deal with trauma from a more humanistic perspective.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.155-175
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• 2017

As social data become into the spotlight, mainstream web search engines provide data indicate how many people searched specific keyword: Web Search Traffic data. Web search traffic information is collection of each crowd that search for specific keyword. In a various area, web search traffic can be used as one of useful variables that represent the attention of common users on specific interests. A lot of studies uses web search traffic data to nowcast or forecast social phenomenon such as epidemic prediction, consumer pattern analysis, product life cycle, financial invest modeling and so on. Also web search traffic data have begun to be applied to predict tourist inbound. Proper demand prediction is needed because tourism is high value-added industry as increasing employment and foreign exchange. Among those tourists, especially Chinese tourists: Youke is continuously growing nowadays, Youke has been largest tourist inbound of Korea tourism for many years and tourism profits per one Youke as well. It is important that research into proper demand prediction approaches of Youke in both public and private sector. Accurate tourism demands prediction is important to efficient decision making in a limited resource. This study suggests improved model that reflects latest issue of society by presented the attention from group of individual. Trip abroad is generally high-involvement activity so that potential tourists likely deep into searching for information about their own trip. Web search traffic data presents tourists' attention in the process of preparation their journey instantaneous and dynamic way. So that this study attempted select key words that potential Chinese tourists likely searched out internet. Baidu-Chinese biggest web search engine that share over 80%- provides users with accessing to web search traffic data. Qualitative interview with potential tourists helps us to understand the information search behavior before a trip and identify the keywords for this study. Selected key words of web search traffic are categorized by how much directly related to "Korean Tourism" in a three levels. Classifying categories helps to find out which keyword can explain Youke inbound demands from close one to far one as distance of category. Web search traffic data of each key words gathered by web crawler developed to crawling web search data onto Baidu Index. Using automatically gathered variable data, linear model is designed by multiple regression analysis for suitable for operational application of decision and policy making because of easiness to explanation about variables' effective relationship. After regression linear models have composed, comparing with model composed traditional variables and model additional input web search traffic data variables to traditional model has conducted by significance and R squared. after comparing performance of models, final model is composed. Final regression model has improved explanation and advantage of real-time immediacy and convenience than traditional model. Furthermore, this study demonstrates system intuitively visualized to general use -Youke Mining solution has several functions of tourist decision making including embed final regression model. Youke Mining solution has algorithm based on data science and well-designed simple interface. In the end this research suggests three significant meanings on theoretical, practical and political aspects. Theoretically, Youke Mining system and the model in this research are the first step on the Youke inbound prediction using interactive and instant variable: web search traffic information represents tourists' attention while prepare their trip. Baidu web search traffic data has more than 80% of web search engine market. Practically, Baidu data could represent attention of the potential tourists who prepare their own tour as real-time. Finally, in political way, designed Chinese tourist demands prediction model based on web search traffic can be used to tourism decision making for efficient managing of resource and optimizing opportunity for successful policy.