• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.26-33
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• 2024

With the start of COVID-19 in 2020, the MBTI test became popular among Korean young generation and then developed into a nationwide hot topic. This paper aims to investigate the characteristics of the MBTI popularity in Korea and the public opinions toward this phenomenon. With the analysis of the reports contents, 231 news reports related to MBTI were selected from KINDS (Korea Integrated News Database System) as research samples. The general attitude of the media towards MBTI tests and the reasons for the formation of positive and negative evaluations will be discussed from three perspectives: media attention, media attitudes and cognitive sources. The research finds that the increasing interest in MBTI among the younger generation in Korea is driven by a post-epidemic desire for self-exploration, emotional planning, and online group affiliation. MBTI has gained quasi-scientific status, similar to horoscopes, influenced by celebrities and a substantial fan base in online communication. While widely used for entertainment and social currency, there are concerns that extensive labeling may unconsciously impact individuals' self-perception and hinder the development of a holistic and objective cognitive framework.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.665-678
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• 2018

The purpose of this study is to analyze the social perception of stepmother in social media and news. For this purpose, we analyzed the texts that were searched as 'stepmother' in Twitter and news articles. The main research results are as follows. The public perception is divided into two types: strengthening the negative image of the stepmother, and providing a positive alternative message to the negative image. Negative images were reported in the media as negative stereotypes about remarried families, as well as images of negative stepmother that afflicts stepchildren like fairy tales. Positive alternative messages were concerned about the negative perception of remarried families. Based on the results of this study, we discussed alternatives to avoid prejudice against stepmother.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.172-181
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• 2020

This study examines the fact-check coverage provided by the SNU fact-check center site(factcheck.snu.ac.kr). A total of 50 articles that were cross-checked by multiple news media organizations were analyzed. The study's variables were topics, types, characteristics, consistency of the news media organizations' judgement, and fact-check sources. This study found that fact-checking coverage was generally focused on presidential or general election candidates or politicians, as well as political topics. The types of fact-checking coverage primarily included factual information, as well as some opinions or interpretations. Fact-check coverage was mainly focused on the facts of the statements themselves, causal relationships, or the timing or target of the comparison criteria. On average, the fact-checking coverage most frequently assigned the judgment 'mostly false, and primarily used interviews of individuals or data from organizations involved in the issue, government data, and experts' statements as the bases for its fact-checking judgements.

• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.421-431
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• 2018

The purpose of this study is to analyze the trends of 'traditional' terminology in Korea. We focus on an empirical investigation of how media reports are conveying 'tradition' terminology in our society by applying text mining and social network analysis techniques. The analysis covered 2,481,143 news articles related to 'tradition' terminology that appeared in the media since the 1920's. In this research, frequency analysis, association analysis and social network analysis were used on articles related to 'tradition' terminology from 1920 to 2017 by decade. By applying these data science techniques, we can grasp the meaning of social culture phenomenon related 'tradition' with objective and value-neutral position and understand the social symbolism which contains the tradition of the times.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.71-85
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• 2004

Many online content providers who use the Internet to distribute contents, such as news, music, games, books, and other types of information, have been experiencing an extremely competitive business environment. To survive in this environment, they have started charging a fee for the contents that they provide. However, there have been very few success stories in commercializing online contents. One of the biggest hurdles may be customers' psychological resistance against paying a fee for the contents that have been free of charge previously. Without examining customers' perceived prices for online contents, many online content providers have tended to decide their prices by themselves. Online games are not exceptional cases. Although many online game-related research works have focused on psychological and technical aspects, very few works have examined online garners' preference carefully. This study alms at exploring online garners' preference by measuring their WTP (willingness to pay) for online games.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.446-458
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• 2018

The media is not just a means of conveying social reality, but is also a political economic subject that restructures social reality. The perceptions and attitudes of the people who read the news can be influenced by the content and direction of the media. Therefore, it is very important to understand and discuss the characteristics of news coverage produced by media. In the case of issues closely related to economic benefits rather than general socio-economic issues, more objective arguments and confirmation of facts are required. In this study, we tried to understand how real estate policy, which is one of the major political and economic issues of S. Korean society, is covered in the media. After analyzing media coverage, we concluded that it was somewhat unreasonable to look at facts about real estate policy objectively and make realistic alternatives, because the framework and attitudes expressed in the articles varied by newspaper.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Information Processing Systems
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• v.14 no.4
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• pp.904-915
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• 2018

We demonstrate how social media content can be used to predict the unemployment rate, a real-world indicator. We present a novel method for predicting the unemployment rate using social media analysis based on natural language processing and statistical modeling. The system collects social media contents including news articles, blogs, and tweets written in Korean, and then extracts data for modeling using part-of-speech tagging and sentiment analysis techniques. The autoregressive integrated moving average with exogenous variables (ARIMAX) and autoregressive with exogenous variables (ARX) models for unemployment rate prediction are fit using the analyzed data. The proposed method quantifies the social moods expressed in social media contents, whereas the existing methods simply present social tendencies. Our model derived a 27.9% improvement in error reduction compared to a Google Index-based model in the mean absolute percentage error metric.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.475-486
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• 2020

The purpose of present study is to identify the regional tourism resources using Webometric network analysis. The study focuses on Suseong area in Daegu metropolitan city. Various kinds of web-based data, for example, hit counts, online news, and public comments, were used to discover hot places and people's responses. The research question is, 'First, what is the optimum level of the search engine for suseong? Second, what is the online appearance of tourist resources in suseong? Which region is the center of tourism with high levels of emergence? Third, what are the main contents of news articles and comments related to the Suseong pond?'. The results show that the search engine optimization level in Suseong is lower than that in other areas in Daegu. In other words, tourism information and contents regarding Suseong are not highly visible on cyber space. Importantly, Suseong pond had the highest online presence. A close analysis of both online news and users' comments on Suseong pond, however, revealed the biggest concern as calling for improving public accessibility to tourism infrastructure. The findings are expected to contribute to policy development and service operation related to tourism resources in Suseong.

• Korean Management Science Review
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• v.25 no.1
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• pp.123-138
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• 2008

Recently, DMB service markets experience a rapid change with terrestrial DMB test-broadcasting for the nation-wide coverage and paid interactive data broadcasting being offered utilizing TPEG and BIFS technologies. This warrants a reexamination of a consumers' adoption intentions for DMB service. This paper uses a survey data set to analyze DMB adoption intentions and the choice between terrestrial DMB and satellite DMB services according to preferred contents and other media usage characteristics. Empirical results show that consumer who prefer TV, music, and movie contents are more likely to adopt DMB service, whereas consumers with high intentions for HSDPA subscription are less likely to adopt DMB service. This implies that continuing development of killer application and the analysis of substitutes or complements of other media are crucial for the increase of DMB adoption intentions. It is found that the more consumers prefer sports, movies and entertainment/game and put higher values in the quality of the contents, the more likely they adopt satellite DMB service. Meanwhile, the more consumers prefer TV, drama and news contents, and are sensitive to the subscription fees, they are more likely to adopt terrestrial DMB service. Therefore, it seem that consumers' DMB adoption between terrestrial and satellite services is crucially related with types and characteristics of contents offered.