• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.67-101
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• 2014

The use of new technology greatly shapes the marketing strategies used by companies to engage their consumers. Among these new technologies, social media is used to reach out to the organization's audience online. One of the most popular social media channels to date is the microblogging platform Twitter. With 500 million tweets sent on average daily, the microblogging platform is definitely a rich source of data for researchers, and a lucrative marketing medium for companies. Nonetheless, one of the challenges for companies in developing an effective Twitter campaign is the limited theoretical and empirical evidence on the proper organizational usage of Twitter despite its potential advantages for a firm's external communications. The current study aims to provide empirical evidence on how firms can utilize Twitter effectively in their marketing communications using the association between brand personality and brand engagement that several branding researchers propose. The study extends Aaker's previous empirical work on brand personality by applying the Brand Personality Scale to explore whether Twitter brand communities convey distinctive brand personalities online and its influence on the communities' level or intensity of consumer engagement and sentiment quality. Moreover, the moderating effect of the product involvement construct in consumer engagement is also measured. By collecting data for a period of eight weeks using the publicly available Twitter application programming interface (API) from 23 accounts of Twitter-verified business-to-consumer (B2C) brands, we analyze the validity of the paper's hypothesis by using computerized content analysis and opinion mining. The study is the first to compare Twitter marketing across organizations using the brand personality concept. It demonstrates a potential basis for Twitter strategies and discusses the benefits of these strategies, thus providing a framework of analysis for Twitter practice and strategic direction for companies developing their use of Twitter to communicate with their followers on this social media platform. This study has four specific research objectives. The first objective is to examine the applicability of brand personality dimensions used in marketing research to online brand communities on Twitter. The second is to establish a connection between the congruence of offline and online brand personalities in building a successful social media brand community. Third, we test the moderating effect of product involvement in the effect of brand personality on brand community engagement. Lastly, we investigate the sentiment quality of consumer messages to the firms that succeed in communicating their brands' personalities on Twitter.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.33-49
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• 2018

The impact of TV Drama success on TV Rating and the channel promotion effectiveness is very high. The cultural and business impact has been also demonstrated through the Korean Wave. Therefore, the early prediction of the blockbuster success of TV Drama is very important from the strategic perspective of the media industry. Previous studies have tried to predict the audience ratings and success of drama based on various methods. However, most of the studies have made simple predictions using intuitive methods such as the main actor and time zone. These studies have limitations in predicting. In this study, we propose a model for predicting the popularity of drama by analyzing the customer's viewing pattern based on various theories. This is not only a theoretical contribution but also has a contribution from the practical point of view that can be used in actual broadcasting companies. In this study, we collected data of 280 TV mini-series dramas, broadcasted over the terrestrial channels for 10 years from 2003 to 2012. From the data, we selected the most highly ranked and the least highly ranked 45 TV drama and analyzed the viewing patterns of them by 11-step. The various assumptions and conditions for modeling are based on existing studies, or by the opinions of actual broadcasters and by data mining techniques. Then, we developed a prediction model by measuring the viewing-time distance (difference) using Euclidean and Correlation method, which is termed in our study similarity (the sum of distance). Through the similarity measure, we predicted the success of dramas from the viewer's initial viewing-time pattern distribution using 1~5 episodes. In order to confirm that the model is shaken according to the measurement method, various distance measurement methods were applied and the model was checked for its dryness. And when the model was established, we could make a more predictive model using a grid search. Furthermore, we classified the viewers who had watched TV drama more than 70% of the total airtime as the "passionate viewer" when a new drama is broadcasted. Then we compared the drama's passionate viewer percentage the most highly ranked and the least highly ranked dramas. So that we can determine the possibility of blockbuster TV mini-series. We find that the initial viewing-time pattern is the key factor for the prediction of blockbuster dramas. From our model, block-buster dramas were correctly classified with the 75.47% accuracy with the initial viewing-time pattern analysis. This paper shows high prediction rate while suggesting audience rating method different from existing ones. Currently, broadcasters rely heavily on some famous actors called so-called star systems, so they are in more severe competition than ever due to rising production costs of broadcasting programs, long-term recession, aggressive investment in comprehensive programming channels and large corporations. Everyone is in a financially difficult situation. The basic revenue model of these broadcasters is advertising, and the execution of advertising is based on audience rating as a basic index. In the drama, there is uncertainty in the drama market that it is difficult to forecast the demand due to the nature of the commodity, while the drama market has a high financial contribution in the success of various contents of the broadcasting company. Therefore, to minimize the risk of failure. Thus, by analyzing the distribution of the first-time viewing time, it can be a practical help to establish a response strategy (organization/ marketing/story change, etc.) of the related company. Also, in this paper, we found that the behavior of the audience is crucial to the success of the program. In this paper, we define TV viewing as a measure of how enthusiastically watching TV is watched. We can predict the success of the program successfully by calculating the loyalty of the customer with the hot blood. This way of calculating loyalty can also be used to calculate loyalty to various platforms. It can also be used for marketing programs such as highlights, script previews, making movies, characters, games, and other marketing projects.

• Korean Security Journal
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• no.1
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• pp.371-408
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• 1997

This article is the reserch on actual condition of crime of arson which occurs in Korea and its countermeasures. The the presented problem in this article are that (1) we have generally very low rate concern about the crime of arson contrary to realistic problems of rapid increase of crime of arson (2) as such criminal motives became so diverse as to the economic or criminal purpose unlike characteristic and mental deficiency of old days, and to countermeasure these problems effectively it presentation the necessity of systemantic research. Based on analysis of reality of arson, the tendency of this arson in Korea in the ratio of increase is said to be higher than those in violence crime or general fire rate. and further its rate is far more greater than those of the U.S.A. and Japan. Arson is considered to be a method of using fire as crime and in case of presently residence to be the abject, it is a public offense crime which aqccompany fatality in human life. This is the well It now fact to all of us. And further in order to presentation to the crime of arson, strictness of criminal law (criminal law No, 164 and 169, and fire protection law No. 110 and 111) and classification of arsonist as felony are institutionary reinforced to punish with certainty of possibility, Therefore, as tendency of arson has been increased compared to other nations, it is necessary to supplement strategical policy to bring out overall concerns of the seriousness of risk and damage of arson, which have been resulted from the lack of understanding. In characteristics analysis of crime of arson, (1) It is now reveald that, in the past such crime rate appeared far more within the boundary of town or city areas in the past, presently increased rate of arsons in rural areas are far more than in the town or small city areas, thereby showing characteristics of crime of arson extending nation wide. (2) general timetable of arson shows that night more than day time rate, and reveald that is trait behavior in secrecy.(3) arsonists are usually arrested at site or by victim or report of third person(82,9%).Investigation activities or self surrenders rate only 11.2%. The time span of arrest is normally the same day of arson and at times it takes more than one year to arrest. This reveals its necessity to prepare for long period of time for arrest, (4) age rate of arson is in their thirties mostly as compared to homicide, robbery and adultery, and considerable numbers of arsons are in old age of over fifties. It reveals age rate is increased (5) Over half of the arsonists are below the junior high school (6) the rate of convicts by thier records is based on first offenders primarily and secondly more than 4 time convicts. This apparently shows necessity of effective correctional education policy for their social assimilation together with re-investigation of human education at the primary and secondary education system in thier life. The examples of motivation for arosnits, such as personal animosity, fury, monetary swindle, luscious purpose and other aims of destroying of proof, and other social resistance, violence including ways of threatening, beside the motives of individual defects, are diverse and arsonic suicide and specifically suicidal accompany together keenly manifested. When we take this fact with the criminal theory, it really reveals arsons of crime are increasing and its casualities are serious and a point as a way of suicide is the anomie theory of Durkheim and comensurate with the theory of that of Merton, Specifically in the arson of industrial complex, it is revealed that one with revolutionary motive or revolting motive would do the arsonic act. For the policy of prevention of arsons, professional research work in organizational cooperation for preventive activities is conducted in municipal or city wise functions in the name of Parson Taskforces and beside a variety of research institutes in federal government have been operating effectively to countermeasure in many fields of research. Franch and Sweden beside the U.S. set up a overall operation of fire prevention research funtions and have obtained very successful result. Japan also put their research likewise for countermeasure. In this research as a way of preventive fire policy, first, it is necessary to accomodate the legal preventitive activities for fire prevention in judicial side and as an administrative side, (1) precise statistic management of crime of arson (2) establishment of professional research functions or a corporate (3) improvement of system for cooperative structural team for investigation of fires and menpower organization of professional members. Secondly, social mentality in individual prospect, recognition of fires by arson and youth education of such effect, educational program for development and practical promotion. Thirdly, in view of environmental side, the ways of actual performance by programming with the establishment of cooperative advancement in local social function elements with administrative office, habitants, school facilities and newspapers measures (2) establishment of personal protection where weak menpowers are displayed in special fire prevention measures. These measures are presented for prevention of crime of arson. The control of crime and prevention shall be prepared as a means of self defence by the principle of self responsibility Specifically arsonists usually aims at the comparatively weak control of fire prevention is prevalent and it is therefore necessary to prepare individual facilities with their spontaneous management of fire prevention instead of public municipal funtures of local geverment. As Clifford L. Karchmer asserted instead of concerns about who would commit arson, what portion of area would be the target of the arson. It is effective to minister spontaveously the fire prevention measure in his facility with the consideration of characteristics of arson. On the other hand, it is necessary for the concerned personnel of local goverment and groups to distribute to the local society in timely manner for new information about the fire prevention, thus contribute to effective result of fire prevention result. In consideration of these factors, it is inevitable to never let coincide with the phemonemon of arsons in similar or mimic features as recognized that these could prevail just an epedemic as a strong imitational attitude. In processing of policy to encounter these problems, it is necessary to place priority of city policy to enhancement of overall concerns toward the definitive essense of crime of arson.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.