As more people share their opinions in online communities, such as Internet portals and social networking services, more opinions are manipulated for the benefit of particular individuals and groups. In particular, when manipulations occur for political purposes, they influence election results as well as government policies and the quality of life. This type of manipulation has targeted the general public, and their analysis and detection has also focused on such manipulation. However, to more efficiently spread propaganda, recent manipulations have targeted common interest groups(e.g., a group of those interested in real estate) and propagated information whose content and style are customized to those groups. This work characterizes such manipulations on common interest groups and proposes method to detect manipulations. To this end, we collected and analyzed opinions posted on 10 common interest groups before and after an election. As a result, we found that manipulations on common interest groups indeed occurred and were gradually increasing toward the election date. We also proposed a detection system that examines individual opinions, their authors, and their collaborators. Using the collected opinions, we demonstrated that the proposed system can accurately classify more than 90% of manipulated opinions and that many of these opinions were posted by multiple collaborators. We believe that regular audits of opinions using the proposed system can quickly isolate manipulations and decrease their impact. Moreover, the proposed features can be used to identify manipulations in domains other than politics.
The purpose of this study is to examine the current operation condition of fashion start-up companies and the characteristics of their founders in Fashion Creative Studio that is one of government programs supporting fashion start-up of rising fashion designer's brands in Korea and one of supporting facilities. For this purpose, this study surveyed 32 fashion start-up companies founders in Busan Fashion Creative Studio and analyzed the data based on the survey. The results are as follows. First of all, 82% of the founders have experience to start their business in 20s and 60% of founders with not more than 3 to 5 years of work experience related to fashion challenge to start a business. Secondly, major distribution channels of the fashion start-up companies are mainly on-line open-market consisting of 36% and SNS is up to 80% as the main promotion method. In addition, exports to China account for 71% of all exports. Lastly, 33% of businesses consider viral marketing by influencer and 50% of them make plan to export their items to East Asia. It is of research significance that this study can suggest the successful direction of establishing and operating fashion start-up companies through making good use of Fashion Creative Studio, the supporting program including facility.
Journal of Korean Home Economics Education Association
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v.33
no.2
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pp.81-93
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2021
The purpose of this study was to analyze the image, perception, and preference type of high school students of Hanbok and examine the differences according to gender and participation in Hanbok classes. For this purpose, a survey was conducted with 438 high school students in Busan. Frequency analysis, chi-square test, t-test, and F-test were performed using the SPSS and the results were as follows. Firstly, for most high school students, Hanbok has an elegant image, but it was also confirmed that they perceive Hanbok to have a splendid image due to its exposure in mass media and SNS. The image of Hanbok differed by gender and participation in Hanbok classes. A higher percentage of male students than female students perceived Hanbok to have rustic image. Secondly, the type of hanbok that high school students prefer was traditional Hanbok, followed by fusion Hanbok, casual Hanbok, and fashion Hanbok. Hanbok preference type differed by gender and participation in classes. Group participating in hanbok classes showed a higher preference for fashion Hanbok than those who did not. Thirdly, high school students' perception of traditional Hanbok was above average. By subcomponents, it was shown in the order of 'esthetics', 'sustainability', and 'practicality'. It was found that there were statistically significant differences in traditional Hanbok perception according to gender and participation in Hanbok classes. Female students evaluated more positively for traditional Hanbok than male students and students who participate in Hanbok classes evaluated traditional Hanbok more positively than non-participating students.
In traditional criminal cases, there is a limit to information collection because information on the subject of investigation is provided only with personal information held by the national organization of legal. Surface web-based OSINT(Open Source Intelligence), including SNS and portal sites that can be searched by general search engines, can be used for meaningful profiling for criminal investigations. The Korean-style OSINT workflow can effectively profile based on OSINT, but in the case of individuals, OSINT that can be collected is limited because it begins with "name", and the reliability is limited, such as collecting information of the persons with the same name. In order to overcome these limitations, this paper defines information related to individuals, i.e., equivalent information, and enables efficient and accurate information collection based on this. Therefore, we present an improved workflow that can extract information related to a specific person, ie., equivalent information, from OSINT. For this purpose, different workflows are presented according to the person's profile. Through this, effective profiling of a person (individuals) is possible, thereby increasing reliability in collecting investigation information. According to this study, in the future, by developing a system that can automate the analysis process of information collected using artificial intelligence technology, it can lay the foundation for the use of OSINT in criminal investigations and contribute to diversification of investigation methods.
Journal of the Korea Society of Computer and Information
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v.27
no.3
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pp.183-199
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2022
With the consumption of smart phone content increasing rapidly, the short clip market in China is rapidly growing. TikTok, a short clip platform, has achieved great business success. However, there is not much research done on TikTok platform from the customers' perspective. To this end, this study aimed to verify the relationship between the social network characteristics on the TikTok platform, attachment toward the TikTok platform, user participation, social identity, psychological distance and reuse intention through an empirical investigation. In August 2021, a survey was conducted on consumers on the subject of TikTok platform in China. The results of the study are as follows. First, the social network characteristics significantly affected the user participation and the attachment. Second, both the attachment and the user participation had a significant impact on reuse intention. Third, user participation had a significant impact on attachment. Fourth, social identity played a significant moderating role in the relationship between social network characteristics and user participation. Fifth, Psychological distance played a significant moderating role in the relationship between social network characteristics and attachment. The results of this study are expected to provide theoretical and practical implications for research on TikTok platform.
The purpose of this study was to investigate the relationship between depression due to the COVID-19 pandemic and park use behaviors using on line posts. During the period of the pandemic prevention activities, text data containing both 'park' and 'depression' were collected from blogs and cafes in the search engine of Naver and Daum, then analyzed using Text Mining and Social Network techniques. As a result, the main usage behaviors of park users who mentioned depression were 'look', 'stroll(walk)' and 'eat'. Other types of behaviors were connected centering around 'look', one of the communication behaviors. Also, from CONCOR analysis, as the cluster referred from communication behavior and dynamic behavior was formed as a single behavior type, it was considered park users with depression perceived the park as the space for communication and physical activities. As the spread of COVID-19 caused the restriction of communication activities, the users might consider parks as one of the solutions. In addition, it was considered that passive usage behaviors have prevailed rather than active ones due to the depression. Resulting outcomes would be useful to plan helpful urban park for citizens. It is necessary to further analyze the park use behavior of users in relation to the period of before/after the COVID-19 pandemic and the existence/nonexistence of depression.
Journal of Korea Entertainment Industry Association
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v.15
no.2
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pp.99-109
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2021
The purpose of this paper is to look at web entertainment in terms of marketing and analyze how consumers in Korea and abroad feel about it. To this end, methods such as literature research, case studies, and consumer interviews were used. The main conclusions of this paper are as follows. First of all, through the case of "Run BTS," the web entertainment program actively reflects the needs of viewers on entertainment content by utilizing the unique interactions of web entertainment in terms of products. In terms of price, web entertainment operated a paid service that contained more diverse contents. However, the degree of satisfaction with paid services was different for each age group or income of viewers. In terms of distribution, web entertainment can position viewers much more clearly than conventional TV entertainment, has strong communication with viewers, and is relatively free from political conflict or censorship in overseas exports. Finally, in terms of public relations, web entertainment is promoted in various ways to fans who are the mainstay of existing viewers, but public relations for various viewers other than fans are relatively weak. Based on the above analysis, this paper proposed ways to improve consumers of web entertainment by region, customized marketing by age, professional window for consumers to directly express their opinions on content, and wide promotion through various media.
University Identity can effectively convey the core values for which schools aim by establishing university identity and integrating one unique image. Therefore, most universities are actively implementing promotional strategies such as newly defining university identity or releasing cultural products. Recently, university brands have been continuously exposed and differentiated through SNS such as Instagram, YouTube, and Facebook as well as existing advertisements and homepages. This study analyzes the identities of the top 80 universities in Korea and China, by referring to the rankings of Asian universities in the 2021 QS World University Rankings, and addresses differences in terms of design shape, number of colors, and use of English. Moreover, 'Cohen's Kappa' consistency analysis was applied to secure data accuracy by analyzing the difference in visual expression of university identity between the two countries through quantification and cross-analysis of visualized university identity design of Korean and Chinese universities. As a result of the study, it is creative, irregular, and has a lot of use of blue, red, and green, and most of them can be seen in less than two colors. In addition, it turns out that word marks and abstract forms of expression are used for university identity design. This study can present implications as effective basic data for internationalizing universities and creating differentiated university identity designs in the future.
Journal of the Korean BIBLIA Society for library and Information Science
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v.32
no.4
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pp.189-212
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2021
The purpose of this study is to analyze an usage behavior for the public library website through web traffic. For this purpose, using Google Analytics and growth hacking technique, the data of A public library website log was analyzed for three months from August 1, 2021 to October 31, 2021. As a result of the study, the young age group of 18-24 years old and 25-34 years old recorded a high rate of new member registration, & it was found that the inflow rate through SNS was high for external inflows. As a result of analysis for the access rate by time, it was found that the time with the highest inflow rate was between 10 am and 11 am both on Wednesday and Friday. As a access channel, the access rate using mobile (64.90%) was quite high, but at the same time, the bounce rate (27.20%) was higher than the average (24.93%), & the rate of duration time (4 minutes 33 seconds) was lower than thee average (5 minutes 22 seconds). Finally, it was found that the utilization rate of reading program events and online book curation service, which the library focuses on producing and promoting, is very low. These research results can be used as basic data for future improvement of public library websites.
Recently, the recommender system has been widely used in various fields such as movies, music, online shopping, and social media, and in the meantime, the recommender model has been developed from correlation analysis through the Apriori model, which can be said to be the first-generation model in the recommender system field. In 2005, many models have been proposed, including deep learning-based models, which are receiving a lot of attention within the recommender model. The recommender model can be classified into a collaborative filtering method, a content-based method, and a hybrid method that uses these two methods integrally. However, these basic methods are gradually losing their status as methodologies in the field as they fail to adapt to internal and external changing factors such as the rapidly changing user-item interaction and the development of big data. On the other hand, the importance of deep learning methodologies in recommender systems is increasing because of its advantages such as nonlinear transformation, representation learning, sequence modeling, and flexibility. In this paper, among deep learning methodologies, RNN, CNN, and GAN-based models suitable for sequential modeling that can accurately and flexibly analyze user-item interactions are classified, compared, and analyzed.
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