Financial Fraud Detection using Text Mining Analysis against Municipal Cybercriminality (지자체 사이버 공간 안전을 위한 금융사기 탐지 텍스트 마이닝 방법)
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- Journal of Intelligence and Information Systems
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- v.23 no.3
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- pp.119-138
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- 2017
Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.
South Korea had a hard time creating its own image of a nation that formed its identity due to 6.25, Japanese-style rule, division of South and North Korea, and military dictatorship. Recently, Korea has been searching and spreading its identity by creating a Korean wave such as various events and K-POPs. However, since there are still no images and cultural products representing Korea's identity, it is necessary to develop design contents related to native culture and professional cultural product design. Design powers such as France and Japan focus on design projects that can add value to their national design policy projects. Traditional Korean contents also need to be specialized and continuous in image design and research. In this study, five lucky-SubokGangnYeon(long life, happiness and peace), a representative of Korean culture, studied with the most interest in the old and the modern, namely, "Living healthy long." Through the development of cultural product design and the use of design content, I would look forward to presenting the diversity and direction in producing Korea's own design products and images that fit the trend of modern 'age of 100.' Based on images based on special exhibitions related to longevity of the National Folk Museum of Korea, the museum discovers key used features and meanings, studies patterns and patterns, and analyzes design cases applied to modern cultural product design. We also want to look at the direction available through design content, which is a symbol of llong life happiness and peace. First, cultural products have limitations that lack the development of design products, lack of public relations and sales outlets, and lack of awareness of traditional culture, which should precede policy support and awareness reform at the national level. Second, we need to streamline prices that meet the needs of the market. Third, cultural product design and contents related to tradition can be settled and disseminated more easily when traditional design is utilized and distributed mainly on practical stationery and household goods. Fourth, it is necessary to develop contents of various Korean images based on research on Korean cultural history and aesthetic consciousness. Research on the Korean culture of designers should be conducted, not just in the form of figurative images. Fifth, traditional manufacturing methods and materials should be respected by modern times, but modern production products should be developed with economy and durability.
Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center.