• Title/Summary/Keyword: News Media

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Optimizing Bit Rate Control for Realtime TV Broadcasting Transmission using LTE Network (LTE 무선통신을 활용한 TV 생방송 중계화면 안정화 비트레이트 조정 연구)

  • Kwon, Mahnwoo;Lim, Hyunchan
    • Journal of Korea Multimedia Society
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    • v.21 no.3
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    • pp.415-422
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    • 2018
  • Advances of telecommunication technology bring various changes in journalism field. Reporters started to gather, edit, and transmit content to main server in media company using hand-held smart media and notebook computer. This paper tried to testify valid bit-rate of visual news content using LTE network and mobile phone. Field news like natural disasters need real-time transmission of video content. But broadcasting company normally use heavy ENG system and transmission satellite trucks. We prepared and experimented different types of visual content that has different bit-rates. Transmission tool was LU-60HD mobile system of LiveU Corporation. Transmission result shows that bit-rate of 2Mbps news content is not suitable for broadcasting and VBR (Variable Bit Rate) transmission has better definition quality than CBR (Constant Bit Rate) method. Three different bit-rate of VBR transmission result shows that 5Mbps clip has better quality than 1Mbps and 3Mbps. The higher bit-rate, the better video quality. But if the content has much movements, that cause delay and abnormal quality of video. So optimizing the balance between stability of signal and quality of bit-rate is crucial factor of real-time broadcasting news gathering business.

Text-Mining Analyses of News Articles on Schizophrenia (조현병 관련 주요 일간지 기사에 대한 텍스트 마이닝 분석)

  • Nam, Hee Jung;Ryu, Seunghyong
    • Korean Journal of Schizophrenia Research
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    • v.23 no.2
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    • pp.58-64
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    • 2020
  • Objectives: In this study, we conducted an exploratory analysis of the current media trends on schizophrenia using text-mining methods. Methods: First, web-crawling techniques extracted text data from 575 news articles in 10 major newspapers between 2018 and 2019, which were selected by searching "schizophrenia" in the Naver News. We had developed document-term matrix (DTM) and/or term-document matrix (TDM) through pre-processing techniques. Through the use of DTM and TDM, frequency analysis, co-occurrence network analysis, and topic model analysis were conducted. Results: Frequency analysis showed that keywords such as "police," "mental illness," "admission," "patient," "crime," "apartment," "lethal weapon," "treatment," "Jinju," and "residents" were frequently mentioned in news articles on schizophrenia. Within the article text, many of these keywords were highly correlated with the term "schizophrenia" and were also interconnected with each other in the co-occurrence network. The latent Dirichlet allocation model presented 10 topics comprising a combination of keywords: "police-Jinju," "hospital-admission," "research-finding," "care-center," "schizophrenia-symptom," "society-issue," "family-mind," "woman-school," and "disabled-facilities." Conclusion: The results of the present study highlight that in recent years, the media has been reporting violence in patients with schizophrenia, thereby raising an important issue of hospitalization and community management of patients with schizophrenia.

A Study of Users' Ideological Propensity in the Comments of Online News: Focusing upon the Stories of the Web Portal Sites and the Press Website News Related to the 20th presidential Election (온라인 뉴스 댓글에 나타난 뉴스 이용자들의 이념적 성향에 관한 연구: 포털과 언론사닷컴의 20대 대선 관련 뉴스기사를 중심으로)

  • Kwang Soon Park;Jong Mook Ahn
    • Journal of Industrial Convergence
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    • v.20 no.12
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    • pp.135-143
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    • 2022
  • This paper aims to grasp what propensity users have in their ideology from the comments in the Web Portal News and the Press Website News. Through these analytical results, the political propensities of not only the Web Portal News and the Press Website News but also the voters who use these news media could be grasped. The collection of data necessary for this study has been made from the comments of 174 news stories for about 90 days before the election day. For the analysis, T-test has been used in order to compare Naver News with Daum News, the Minjoo Party of Korea with the People Power Party, and the Press Web Site News with Naver News. As a result of the analysis, the comments of Naver News took the higher percentage in the positive writings about the candidates of the conservative party. but, in contrast, those of Daum News in that percentage were higher about the ones of the progressive party. Accordingly, it can be found that Naver News is mainly used by users with the politically conservative propensity, while Daum News is mostly used by those with progressive one.

The Impact of Individuals' Political Tendency on the Perception of Reliability and Social Impact of Online Newspaper Comments (개인의 정치성향이 뉴스 댓글에 대한 신뢰성과 사회적 영향력의 인식에 미치는 영향)

  • Lee, Zoon-Ky;Han, Mi-Ae
    • The Journal of Society for e-Business Studies
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    • v.17 no.1
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    • pp.173-187
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    • 2012
  • As newspapers which have been major news media are being replaced by on-line news media in recent years, many researchers are paying attention to "comments(news users' short remarks on an article)", a newly emerged way of forming public opinion. This study is examining how the similarity between political disposition of on-line news visitors and that of news media impacts upon their evaluation on quality of comments from the viewpoint of 'social identity theory.' This study may have academic significance because it inspected the pattern of media usage and the cognition of comments in relation to political disposition for the first time and showed 'comments reading' and the function of comments to form public opinion(comments journalism).

Semantic Network Analysis of Online News and Social Media Text Related to Comprehensive Nursing Care Service (간호간병통합서비스 관련 온라인 기사 및 소셜미디어 빅데이터의 의미연결망 분석)

  • Kim, Minji;Choi, Mona;Youm, Yoosik
    • Journal of Korean Academy of Nursing
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    • v.47 no.6
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    • pp.806-816
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    • 2017
  • Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.

COVID-19, Social Distancing and Social Media: Evidence from Twitter and Facebook Users in Korea

  • Jin Seon Choe;Jaecheol Park;Sojung Yoon
    • Asia pacific journal of information systems
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    • v.30 no.4
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    • pp.785-807
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    • 2020
  • The novel Coronavirus disease 2019 (COVID-19) is unprecedentedly changing the world since its outbreak in late 2019. Using the collected the data related to COVID-19 and the social media user data from a mobile application market research agency from January 25 to April 7, this study empirically examines the effect of the number of confirmed COVID-19 cases worldwide, the number news COVID-19, and the enforcement of social distancing measures on the daily active users (DAU) of two social media services - Twitter and Facebook - in South Korea. There are three important findings from the results of econometric analysis. First, the number of confirmed COVID-19 cases worldwide has a negative effect on the DAU of social media. Second, the number of COVID-19 news is negatively associated with the DAU of social media. Finally, the implementation of social distancing measures has no significant effect on the DAU of the social media. Theoretical implications and managerial guidelines are also discussed.

Millennial Generation's Mobile News Consumption and the Impact of Social Media (밀레니얼세대의 모바일 뉴스소비와 소셜미디어의 영향)

  • Seol, Jinah
    • Journal of Internet Computing and Services
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    • v.19 no.4
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    • pp.123-133
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    • 2018
  • This paper examined how the millennial generation consumes mobile news through social networking sites with regards to user patterns, preference topics and news values, and whether news topics and news values may influence their overall mobile SNS news consumption and interactivity. The findings show that more than 2/3 of respondents consumed mobile SNS news at least once everyday for 30minutes to one-hour. Male millennials tended to use Facebook and Kakao-talk more than female. While the portal site was the most accessed channel for consuming mobile news, SNS was the second, more than the combined use of national daily papers, TV, and internet newspapers. The respondents' demographic characteristics and news topics also affect the form and degree of news interactivity. With regards to their preferences and prioritization of news values, millennials tend to perceive 'impact' and 'usefulness' as being most important, despite the differences of their demographic characteristics. They also preferred those news values most. There were significant differences in terms of preferred news topics according to the demographics' characteristics.

Body of Actress, Power and Resistance : focused on SBS News on Jang Ja-Yeon's Letters (여배우의 몸과 권력, 그리고 저항: SBS의 고 장자연 자필편지사건 관련보도를 중심으로)

  • Hong, Sook-Yeong
    • The Journal of the Korea Contents Association
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    • v.11 no.12
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    • pp.649-657
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    • 2011
  • This study examines how news media covers Jang Ja-Yeon's scandal through analyzing texts and images about Jang Ja-Yeon described in SBS (Seoul Broadcasting System) Eight O'clock News. The study found that the news stories mainly covered lasciviously Jang Ja-Yeon's entertaining service, sexual service, other actresses who were forced to provide entertaining service, a list of people who forced her to serve, death, and vengeance. In addition, Jang Ja-Yeon in the news stories were described as "unknown actress," and she was located into low class and entertained the men in power. The analysis implicated that the body image of actress reflects a merchandize in the news media, and the news media used Ja-Yeon Jang's body image for news value which represents the society of reification, hierarchical and masculine society.

Statistical analysis of mobile internet news users' attributes affecting on opinion formation for social major issues (모바일 인터넷 뉴스 이용자의 속성이 정치, 경제, 사회적 주요 현안에 대한 의견 형성에 미치는 영향에 대한 통계적 분석)

  • Kim, Jaehee
    • 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.

Context Sharing Framework Based on Time Dependent Metadata for Social News Service (소셜 뉴스를 위한 시간 종속적인 메타데이터 기반의 컨텍스트 공유 프레임워크)

  • Ga, Myung-Hyun;Oh, Kyeong-Jin;Hong, Myung-Duk;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.19 no.4
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    • pp.39-53
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    • 2013
  • The emergence of the internet technology and SNS has increased the information flow and has changed the way people to communicate from one-way to two-way communication. Users not only consume and share the information, they also can create and share it among their friends across the social network service. It also changes the Social Media behavior to become one of the most important communication tools which also includes Social TV. Social TV is a form which people can watch a TV program and at the same share any information or its content with friends through Social media. Social News is getting popular and also known as a Participatory Social Media. It creates influences on user interest through Internet to represent society issues and creates news credibility based on user's reputation. However, the conventional platforms in news services only focus on the news recommendation domain. Recent development in SNS has changed this landscape to allow user to share and disseminate the news. Conventional platform does not provide any special way for news to be share. Currently, Social News Service only allows user to access the entire news. Nonetheless, they cannot access partial of the contents which related to users interest. For example user only have interested to a partial of the news and share the content, it is still hard for them to do so. In worst cases users might understand the news in different context. To solve this, Social News Service must provide a method to provide additional information. For example, Yovisto known as an academic video searching service provided time dependent metadata from the video. User can search and watch partial of video content according to time dependent metadata. They also can share content with a friend in social media. Yovisto applies a method to divide or synchronize a video based whenever the slides presentation is changed to another page. However, we are not able to employs this method on news video since the news video is not incorporating with any power point slides presentation. Segmentation method is required to separate the news video and to creating time dependent metadata. In this work, In this paper, a time dependent metadata-based framework is proposed to segment news contents and to provide time dependent metadata so that user can use context information to communicate with their friends. The transcript of the news is divided by using the proposed story segmentation method. We provide a tag to represent the entire content of the news. And provide the sub tag to indicate the segmented news which includes the starting time of the news. The time dependent metadata helps user to track the news information. It also allows them to leave a comment on each segment of the news. User also may share the news based on time metadata as segmented news or as a whole. Therefore, it helps the user to understand the shared news. To demonstrate the performance, we evaluate the story segmentation accuracy and also the tag generation. For this purpose, we measured accuracy of the story segmentation through semantic similarity and compared to the benchmark algorithm. Experimental results show that the proposed method outperforms benchmark algorithms in terms of the accuracy of story segmentation. It is important to note that sub tag accuracy is the most important as a part of the proposed framework to share the specific news context with others. To extract a more accurate sub tags, we have created stop word list that is not related to the content of the news such as name of the anchor or reporter. And we applied to framework. We have analyzed the accuracy of tags and sub tags which represent the context of news. From the analysis, it seems that proposed framework is helpful to users for sharing their opinions with context information in Social media and Social news.