• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.4
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• pp.35-45
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• 2018

Users are sharing many of contents such as text, image, video, and so on in SNS. There are various information as like as personal interesting, opinion, and relationship in social media contents. Therefore, many of recommendation systems or search systems are being developed through analysis of social media contents. In order to extract subject-related topics of social context being collected from social media channels in developing those system, it is necessary to develop ontologies for semantic analysis. However, it is difficult to develop formal ontology because social media contents have the characteristics of non-formal data. Therefore, we develop a social topic system based on semantic and subject correlation. First of all, an extracting system of social topic based on semantic relationship analyzes semantic correlation and then extracts topics expressing semantic information of corresponding social context. Because the possibility of developing formal ontology expressing fully semantic information of various areas is limited, we develop a self-extensible architecture of ontology for semantic correlation. And then, a classifier of social contents and feed back classifies equivalent subject's social contents and feedbacks for extracting social topics according semantic correlation. The result of analyzing social contents and feedbacks extracts subject keyword, and index by measuring the degree of association based on social topic's semantic correlation. Deep Learning is applied into the process of indexing for improving accuracy and performance of mapping analysis of subject's extracting and semantic correlation. We expect that proposed system provides customized contents for users as well as optimized searching results because of analyzing semantic and subject correlation.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.74-85
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• 2019

This Study explores the reason why the social media like Cyworld, Iloveschool in Korea in the viewpoint if the layered model by interview. As a result the success factor in the viewpoint of layered model, user used social media for fulfilling the need for linking with other users and the social media offers the customized contents to user. Finally the social media dominated the market in advance. Facebook and Kakao talk are good examples of successful media. The failure factors are to care less about what other users want, to limit the expand of platform and not to copy with the change of the media environment. Iloveschool, Cyworld and Twitter are the examples of failure social media in Korean society. This study highlights the importance of the sensitivity of the change of environment. The expert mentioned the importance of 4th industrial revolution technology like AI, Big data and expected that new technology will emerge and the service will be developed by the change of user's taste.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1570-1594
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• 2017

Social network services have recently changed from environments for simply building connections among users to open platforms for generating and sharing various forms of information. Existing user reputation computation methods are inadequate for determining the trust in users on social media where explicit ratings are rare, because they determine the trust in users based on user profile, explicit relations, and explicit ratings. To solve this limitation of previous research, we propose a user reputation computation method suitable for the social media environment by incorporating implicit as well as explicit ratings. Reliable user reputation is estimated by identifying malicious information raters, modifying explicit ratings, and applying them to user reputation scores. The proposed method incorporates implicit ratings into user reputation estimation by differentiating positive and negative implicit ratings. Moreover, the method generates user reputation scores for individual categories to determine a given user's expertise, and incorporates the number of users who participated in rating to determine a given user's influence. This allows reputation scores to be generated also for users who have received no explicit ratings, and, thereby, is more suitable for social media. In addition, based on the user reputation scores, malicious information providers can be identified.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6547-6555
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• 2014

This study attempted to verify what motivates fans to follow college sports teams' social media and identify the motivational factors that can best predict fans' social media consumption. Confirmatory Factor Analysis (CFA) indicated that previously identified seven motives for online consumption, i.e., information, diversion, socialization, pass-time, fanship, team support, and technical knowledge, are compatible with the use of college sports teams' social media. In addition, a results of multiple regression found diversion, socialization, fanship, team support, and technical knowledge to significantly predict the level of social media consumption while information and pass-time did not significantly affect social media consumption. In particular, socialization had the greatest influence on social media consumption.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.427-436
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• 2013

Social media is drawing attention among companies for its potential as a marketing tool. There are many types of social media and their characteristics are varied, and thus choosing the appropriate social media considering the purpose of the company is important. In this paper, we conduct comparative analysis on the popular social media such as Facebook, Twitter, Naver blog, Youtube, Cyworld and Me2day using multidimensional scaling method. The result shows that there are differences in the effectiveness of enhancing diverse dimensions of corporate image among social media. This result can be used in developing social media based marketing strategy.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.157-173
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• 2014

In this study, how social media PR marketing affect corporate brand expansion was studied. this study consist of 5 chapters; needs and purposes in 1st, concept& characteristics, development processes, needs of social media and merits&demerits as marketing tool in 2nd. concept& characteristics and merits&demerits of corporate brand expansion in 3rd. examples of social media marketing in domestic&foreign and current statuses in 4th. In final, conclusion of the effect of social media PR marketing on corporate brand expansion were presented in each chapter.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.309-318
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• 2017

This study is for analyzing the tone, the frame and the characteristics of political news in social media. Social news media is not same as old media in sharing news freely by SNS like tweeter, facebook and reporting, editing by anyone using SNS with various opinions. With Content analysis, sampling 419 cases from 'Wikitree' by the keyword, 'presidential election', all the full text analysed each how is social media making public opinion differently and which frame is using in. As the result, the social media has different tone, frame, and characteristic due to the reported figure, type of report, information source, attitude to the government, specifically shows a lack of in-depth report and distinct soft-journalism just same as old media's. Because the tone of social news media is not probable, specific but improbable, vague, using the irrational, strategic and episodic frame mainly.

• Journal of Information Technology Applications and Management
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• v.30 no.4
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• pp.65-76
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• 2023

On social media, companies create brand experiences while customers actively seek, consume, and generate brand-related content. Customer engagement plays a vital role in the marketing performance of social media-driven brands. This study explores the positive relationship between brand authenticity, aligning brand identity with image, and self-brand connection, aligning brand identity with consumers' self-concepts, on customer engagement and its subsequent impact on brand loyalty. The study surveyed 243 consumers engaged with brand-related social media content, validating hypotheses using structural equation modeling. Results confirmed that brand authenticity and self-brand connection positively affect customer engagement, which, in turn, boosts brand loyalty. These findings highlight the importance of companies enhancing brand authenticity and self-brand connection to drive customer engagement, with theoretical and practical implications provided.

• Journal of Contemporary Eastern Asia
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• v.13 no.1
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• pp.69-81
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• 2014

While much in the field of public management has emphasized the importance of nonprofit advocacy activities in policy and decision-making procedures, few have considered the relevance and impact of leading actors on structuring diverse patterns of information sharing and communication through social media. Building nonprofit advocacy is a complicated process for a single organization to undertake, but social media applications such as Facebook and Twitter have facilitated nonprofit organizations and stakeholders to effectively share information and communicate with each other for identifying their mission as it relates to environmental issues. By analyzing the Australian Marine Conservation Society's (AMCS) Twitter network data from the period 1 April to 20 April, 2013, this research discovered diverse patterns in nonprofit advocacy by leading actors in building advocacy. Based on the webometrics approach, analysis results show that nonprofit advocacy through social media is structured by dynamic information flows and intercommunications among participants and followers of the AMCS. Also, the findings indicate that the news media and international and domestic nonprofit organizations have a leading role in building nonprofit advocacy by clustering with their followers.

• Korean Journal of Computational Design and Engineering
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• v.20 no.3
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• pp.254-262
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• 2015

This study proposes an approach to Product Data Management (PDM) education for collaborative product data management, which can support collaborative product development process. This approach introduces social media and a PDM system into a framework for PDM education supported by consistent product development process and product data model. It has been applied to two PDM classes and the result shows that the social media in PDM education can support not only experiences of the collaborative product data management but also interactive and informal communications among instructors and participants using integrated social media with product data during courses.