• Social Workers
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• no.10 s.54
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• pp.56-58
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• 2006

• Social Workers
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• no.9 s.53
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• pp.56-58
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• 2006

• Social Workers
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• no.5 s.37
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• pp.54-58
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• 2005

• Social Workers
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• no.12 s.44
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• pp.52-54
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• 2005

• Social Workers
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• no.7 s.39
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• pp.53-57
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• 2005

• Korean journal of communication and information
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• v.26
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• pp.157-208
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• 2004

This study explored how television news constructed an issue of the building of a nuclear waste facility on Wido, an issue which displayed a social conflict in the latter half of the year 2003. To do this, this study conducted frame analysis on KBS and MBC main news including national and local ones, broadcasted from 11 July, 2003 to 10 December, 2003. It was found that television news tended to stress violent protests against site designation and social disorder rather than the causes of a conflict and its solutions. Therefore, news reporting excluded fundamental reasons of conflict such as the governmental decision-making process of site designation, geological suitability, safety issue and nuclear energy policy, emphasizing the confrontation and clash between pro and con groups of site designation. This indicates that television news defines an issue of the building of a nuclear waste facility as the local conflict between groups, the police and demonstrators, or neighbors who approve and protest the site designation, not as the national issue of nuclear policy.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.57-74
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• 2021

The proliferation of smart devices (such as smart phones and tablet PCs) has led to a marked increase in the use of mobile-based internet. As a result, the influence of the mobile internet has become important to make opinions on social issues. This study explores the effects of mobile internet news users' characteristics on formation of opinions about major political, economic and social issues. We used the data from the media audience awareness survey by the Korean Press Foundation in 2016 and 2017 in this analysis. The characteristics of the news users are gender, age, education, income, news usage days, news usage hours, media application usage days, news gathering application usage days, portal usage days, and media official website usage days. These characteristics are known as possible explanatory variables for the mobile internet news users. Multiple logistic regressions were done with interpretation to know which covariates affect on formation of major opinion.

• 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.

• Korean journal of communication and information
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• v.52
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• pp.5-26
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• 2010

This study explores how major Korean television evening news report, interpret and evaluate the Korean Grand Canal Project(KGCP). For this research, 488 news clips regarding the KGCP are selected among the MBC, KBS and SBS daily evening news. As a result, the findings are as follows: First, the ratios of analyzing reports for MBC, brief reports for KBS, and straight news for SBS are outstanding. At the same time, the three news companies show that they are against the KGCP through the reporting attitudes. However, the most frequently broadcasted news frames is the authoritative political execution for both MBC and KBS, and the political agenda for SBS news respectively. In terms of the most frequently interviewed group for all three news is the government and ruling Grand National Party; they are the most favor of the authoritative political executions and the political agenda news frames. However, the NGO groups and the opposition parties which are against the KGCP support "Process" in terms of the frames activity. Finally, MBC speaks out the frame activity of "Process", supporting the political opposition parties and NGO groups. On the country, both KBS and SBS speak up the government and ruling party, supporting the KGCP, stressing frame activity of "Aspiration". This it concludes that both KBS and SBS are short of the social responsibilities as a social media mediator for the social disputes between the government and the NGO groups, including opposition parties.

• Asian Journal for Public Opinion Research
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• v.8 no.2
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• pp.105-125
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• 2020

The purpose of this paper is to analyze 1) who created and distributed fake news, 2) the distribution channels of fake news, 3) who fake news has targeted, and 4) the effects on voting and the impact of fake news on Korean politics. In South Korea, fake news was mainly created by candidates or election campaigns. The reason is that in the wake of the impeachment of President Park Guen Hye, all the political parties in Korea used fake news as a means of mobilizing supporters for each of their candidates or parties to gain an advantage in situations involving political divisions and confrontations between the pro-impeachment, progressive young generation and anti-impeachment, conservative senior generation. Voters' media usage patterns were polarized through social network services (SNS) media and television. Fake news was mostly received through these two media outlets. According to the spreading structure of fake news in Korea, the younger generation generally uses SNS posts intended for unspecified individuals, and the older generation uses closed SNS like KakaoTalk or Naver's BAND. In the end, it is typically characteristic of the older generation to spread fake news through existing offline human networks. In the 2017 presidential election, fake news has been confirmed to have the effect of mobilizing supporters for each political party. In the presidential election, an increase in voter turnout was confirmed among those in their 20s and those in their 60s or older. Evidently, fake news influenced the election of Moon Jae-In. The influence of fake news is expected to grow further as ideological polarization and consequent political polarization continues to intensify in South Korea.