• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.5
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• pp.567-575
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• 2020

As online social networks are used as a critical medium for modern people's information sharing and relationship, their users are increasing rapidly every year. This not only increases usage but also surpasses the existing media in terms of information credibility. Therefore, emerging marketing strategies are deliberately attacking social networks. As a result, public opinion, which should be formed naturally, is artificially formed by online attacks, and many people trust it. Therefore, many studies have been conducted to detect agents attacking online social networks. In this paper, we analyze the trends of researches attempting to detect such online social network attackers, focusing on researches using social network graph characteristics. While the existing content-based techniques may represent classification errors due to privacy infringement and changes in attack strategies, the graph-based method proposes a more robust detection method using attacker patterns.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.3
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• pp.18-26
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• 2011

Social network services whose users increase rapidly is the online services that reflect social network. They are used for various purposes such as strategy of election, commercial advertisement and marketing, educational information sharing and exchange of medical knowledge and opinions. These services make users form social networks with other users who have common interests and expand their relationships by releasing their personal information and utilizing other users' social networks. However, the social network services based on open and sharing of information raise various security threats such as violation of privacy and phishing. In this paper, we propose a group key management scheme and protocols using key rings to protect communication of small groups in social network services.

• Journal of Digital Convergence
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• v.15 no.6
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• pp.133-143
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• 2017

Data is the most important asset in the financial sector. On average, 71 percent of financial institutions generate competitive advantage over data analysis. In particular, in the card industry, the card transaction data is widely used in the development of merchant information, economic fluctuations, and information services by analyzing patterns of consumer behavior and preference trends of all customers. However, creation of new value through fusion of data is insufficient. This study introduces the analysis and forecasting of consumption trends of credit card companies which convergently analyzed the social data and the sales data of the company's own. BC Card developed an algorithm for linking card and social data with trend profiling, and developed a visualization system for analysis contents. In order to verify the performance, BC card analyzed the trends related to 'Six Pocket' and conducted th pilot marketing campaign. As a result, they increased marketing multiplier by 40~100%. This study has implications for creating a methodology and case for analyzing the convergence of structured and unstructured data analysis that have been done separately in the past. This will provide useful implications for future trends not only in card industry but also in other industries.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.193-200
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• 2021

Recently, posts and opinions on tourist attractions are actively shared on social media. These social big data provide meaningful information to identify objective images of tourist destinations recognized by consumers. Therefore, an in-depth understanding of the tourist image is possible by analyzing these big data on tourism. The study is to analyze destination images in Gangwon-do using big data from social media. It is wanted to understand destination images in Gangwon-do using semantic network analysis and then provided suggestions on how to enhance image to secure differentiated competitiveness as a destination for tourists. According to the frequency analysis results, as tourism in Gangwon-do, Sokcho, Gangneung, and Yangyang were mentioned at a high level in that order, and the purpose of travel was restaurant tour, gourmet food, family trip, vacation, and experience. In particular, it was found that they preferred day trips, weekends, and experiences. Four suggestions were made based on the results. First, it is necessary to develop various types of hotels, accommodation facilities and experience-oriented tour packages. Second, it is necessary to develop a day-to-day travel package that utilizes proximity to the Seoul metropolitan area. Third, it is necessary to promote traditional restaurants and local food. Finally, it is necessary to develop tourist package suitable for healing and family travel. Through this research, the destination image of Gangwon-do was identified and a tourism marketing strategy was presented to improve competitiveness. It also provided a theoretical basis for the use of the big data of tourism consumers in the field of tourism business.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.1-19
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• 2023

Despite the growing importance of video-based social media content, such as vlogs, as a marketing tool in the travel industry, there is limited research on the characteristics that enhance engagement among potential travelers. This study explores the influence of emotional valence in YouTube travel content on viewer engagement, specifically likes and comments. We analyzed 4,619 travel-related YouTube videos from eight popular tourist cities. Using negative binomial regression analysis, we found that both positive and negative emotions significantly influence the number of likes received. Videos with higher positive emotions as well as negative emotions receive more likes. However, when it comes to the number of comments, only negative emotions showed a significant positive influence, while positive emotions had no significant impact. These findings offer valuable insights for marketers seeking to optimize engagement strategies on YouTube, considering the unique nature of travel products. Further research into the effects of specific emotions on engagement is warranted to improve marketing strategies. This study highlights the powerful impact of emotions on viewer engagement in the context of social media, particularly on YouTube.

• Knowledge Management Research
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• v.16 no.2
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• pp.91-111
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• 2015

Social media marketing has gained attention from marketers due to the growing number of social media users. Marketers around the globe have a serious concern over how to utilize social media as a successful marketing tool. Many of them show a lack of understanding of the essential feature of social media and effective social media marketing strategies, which brings about a higher chance of social media marketing failures. Analyzing the failure cases of social media marketing is vital because it provides rich insights for marketing experts who have difficulty in developing effective social media marketing strategies. Therefore, this study conducted multiple case studies by selecting five failure cases of social media marketing which we defined as paradigmatic social media marketing failures which happened in the last five years in South Korea. From the case studies, we derived five successful social media marketing strategies. This study has a theoretical implication because it is the first to suggest effective social media marketing strategies based on the analysis on social media marketing failure cases. It also has a practical implication since it proposes specific social media marketing strategies which can help facilitate successful social media marketing.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.213-214
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• 2016

디자인경영과 서비스디자인 등은 전 산업분야에 걸쳐 이슈가 되고 있으며, 기업의 경쟁력으로서 중요한 요소가 되고 있다. 산업디자인 분야는 제품디자인, 시각디자인, 포장디자인 등으로 분류될 수 있다. 각 분야의 공통점은 제품의 생산부터 유통까지 연계되어 관리되어 지며, 최근에는 저작권, 사회적책임, 시장영향력에 대한 부가적인 업무가 요구되고 있다는 점이다. 본 논문에서는 산업디자인과 관련한 이미지와 오피니언에 기반한 빅데이터를 이용하여 디자인 공급자와 수요자 간의 컨설팅, 디자인제작, 유통, 후속조치 등이 통합적으로 관리될 수 있는 시스템을 제안한다.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.205-210
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• 2019

Alongside the development of communication technologies such as smart phone, 5G, advertisements which have been regarded as nexus of marketing behaviors are treated as surplus entities in our society now. Ad marketers have been focusing on storytelling advertisements via SNS or similar web-services. We are facing another big media changes such as Virtual Reality, Augmented Reality. Especially the current study probes Mixed Reality as the potential key of new storytelling brand marketing with discussing directions and insights based on the narrative transportation theory.

• Smart Media Journal
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• v.12 no.11
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• pp.165-174
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• 2023

This study sought to identify the causal relationship between variables through empirical analysis between Chinese female consumers' beauty SNS marketing, brand image, and brand attitude. Through the results of this study, it was confirmed that a causal relationship exists between each variable. In particular, it was confirmed that interactivity, a sub-factor of beauty SNS marketing, is a key factor influencing the variables of brand image and brand attitude. In addition, accessibility, a sub-factor of beauty SNS marketing, is also an important factor affecting brand image and brand attitude. It was confirmed that vitality and informativeness are important factors influencing brand image and brand attitude in that order.