• Title/Summary/Keyword: Newspapers as Topic

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Analysis of Food and Nutrition Information for Articles and Advertisements in the Daily Newspapers (Year 2002) (일간 신문의 기사와 광고에 나타난 식품영양정보의 현황 조사 (2002년))

  • Mun, Hyeon-Gyeong;Yong, Mi-Jin;Jang, Yeong-Ju
    • Journal of the Korean Dietetic Association
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    • v.10 no.2
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    • pp.143-158
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    • 2004
  • The object of this study is to investigate and analyze the quantity and quality of informations on health, food and nutrition reported by newspapers. Six different major domestic daily newspapers(Hankook Ilbo, Donga IIbo, Chosun IIbo, Kyunghyang Shinmun, Hankyoreh Shinmun, JoongAng Ilbo), were monitored from 1st of May to 31st of Oct. 2002.. The results of monitoring in the newspapers were summarized as follows; 1. The total percentage of the articles on health and food nutrition was 2.7% and the percentage of the advertisements on health, food and nutrition was 17.5% of total area of the newspaper. The ratio of the number of food and nutrition topic on the total number of health and food nutrition topic was 35.8% for the articles, was 62.9% for the advertisements. Among advertisements on food and nutrition, the percentage of advertisements on healthy foods was the highest (3,481 or 55.0%). 2. Contents of 340 articles(26.1%) were reported as suitable informations. Contents of 259 articles(19.9%) were reported as inaccurate informations on health, food and nutrition. In the analysis of advertisements, the number of advertisements without sufficient reliable sources was 2,488 cases(23.0%), and with exaggerated contents was 2,268 cases(21.0%). The articles and advertisements should be backed by scientific research or reliable sources and also the opinions of people with expertise in order to report accurate informations to the general public. In order to achieve these results, there should be continuing monitoring activity for the newspapers.

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News Coverage on COVID-19 and Partisan Agenda-setting: An Analysis of Topic Modeling Results and Survey Data (코로나19 보도와 정파적 의제설정: 토픽모델링과 설문조사 연결분석)

  • Cha, Chae Young;Wang, Yu-Hsiang;Lee, Jong Hyuk
    • The Journal of the Korea Contents Association
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    • v.22 no.1
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    • pp.86-98
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    • 2022
  • This study explored the agenda of conservative and liberal media in reporting COVID-19, and observed the effects of each media's partisan agenda-setting on the public with the same political orientation. To this end, researchers collected 5,286 articles on COVID-19 from five newspapers, and analyzed the survey data of 1,067 respondents. Next, the researchers extracted main agenda using LDA topic modeling and analyzed the correlation between newspapers' agenda and survey respondents' agenda. As results, 15 topics such as infection, vaccine, and economic crisis appeared as the media agenda, and the difference in major agenda between conservative and liberal media was found. On the other hand, the conservative media exerted an agenda-setting influence not only on the conservatives but also on the liberals, but the liberal media did not have a significant influence on the liberals. This study contributes to the methodological expansion of agenda-setting research by introducing a new way to confirm the effectiveness of agenda-setting by combining topic modeling and survey.

Topic Modeling of Korean Newspaper Articles on Aging via Latent Dirichlet Allocation

  • Lee, So Chung
    • Asian Journal for Public Opinion Research
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    • v.10 no.1
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    • pp.4-22
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    • 2022
  • The purpose of this study is to explore the structure of social discourse on aging in Korea by analyzing newspaper articles on aging. The analysis is composed of three steps: first, data collection and preprocessing; second, identifying the latent topics; and third, observing yearly dynamics of topics. In total, 1,472 newspaper articles that included the word "aging" within the title were collected from 10 major newspapers between 2006 and 2019. The underlying topic structure was analyzed using Latent Dirichlet Allocation (LDA), a topic modeling method widely adopted by text mining academics and researchers. Seven latent topics were generated from the LDA model, defined as social issues, death, private insurance, economic growth, national debt, labor market innovation, and income security. The topic loadings demonstrated a clear increase in public interest on topics such as national debt and labor market innovation in recent years. This study concludes that media discourse on aging has shifted towards more productivity and efficiency related issues, requiring older people to be productive citizens. Such subjectivation connotes a decreased role of the government and society by shifting the responsibility to individuals not being able to adapt successfully as productive citizens within the labor market.

Differences of news aspect about Asia and West in Korean newspapers and its reason: Focusing on news topic, amount of news, news tone and media sources (한국신문의 아시아와 서구에 대한 보도양상의 차이와 이유 연구: 뉴스주제, 보도량, 보도태도, 미디어 정보원을 중심으로)

  • Oh, Day-Young
    • Korean journal of communication and information
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    • v.61
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    • pp.74-97
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    • 2013
  • Asia is developing rapidly in 21st century. Human and material exchanges between Korea and Asian countries have greatly increased. Korea entered the multicultural society. It became important for Korean people to understand Asia more correctively. Korean media can play a key role for this. In this point, I analyzed 1786 news contents reported in 2011 by four Korean newspapers(Chosun Ilbo, Dong-A Ilbo, Hankyoreh newspaper, Kyungh Kyunghyang Daily News), to see differences of Asia and West news aspect and its reason, focusing on news topic, amount of news, news tone and foreign media sources. In amount of news, the percent of West(54.3%) was higher than that of Asia news(45.7%). In news tone, negative news were the most in Asia news, but the least in West news. Korean newspaper showed more positive attitude to West than Asia. 1786 news were classified into seven topics(morality and justice, politics, economics and science, society, diplomacy and national defense, human interest, people). In news amount of seven topics, Korean newspapers reported hard news like morality and justice more than soft news like human interest about Asia. However they reported many soft news about West besides hard news. In news topics and tone, hard news showed negative tone most and soft news showed neutral or positive tone most. As a result, Korean news showed the negative attitude to Asia and the positive to West. Among five main sources(media, government, private organization, individual and material), only media source affected the differences of news attitude to Asia and West. Asia media source took the more positive attitude to Asia than West. West media took the negative attitude to Asia most and the neutral attitude to West most. Korean newspapers used West media as main sources in the news of all areas except East Asia. As a result, Korean newspapers showed the West-centered-attitude and reported the negative news more than neutral and positive about Asia. It was suggested that Korean newspapers had better increase Asia news in diverse spheres by the direct reporting of the correspondent and the more use of Asia media through the internet.

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Topic-Network based Topic Shift Detection on Twitter (트위터 데이터를 이용한 네트워크 기반 토픽 변화 추적 연구)

  • Jin, Seol A;Heo, Go Eun;Jeong, Yoo Kyung;Song, Min
    • Journal of the Korean Society for information Management
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    • v.30 no.1
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    • pp.285-302
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    • 2013
  • This study identified topic shifts and patterns over time by analyzing an enormous amount of Twitter data whose characteristics are high accessibility and briefness. First, we extracted keywords for a certain product and used them for representing the topic network allows for intuitive understanding of keywords associated with topics by nodes and edges by co-word analysis. We conducted temporal analysis of term co-occurrence as well as topic modeling to examine the results of network analysis. In addition, the results of comparing topic shifts on Twitter with the corresponding retrieval results from newspapers confirm that Twitter makes immediate responses to news media and spreads the negative issues out quickly. Our findings may suggest that companies utilize the proposed technique to identify public's negative opinions as quickly as possible and to apply for the timely decision making and effective responses to their customers.

Twitter Sentiment Analysis for the Recent Trend Extracted from the Newspaper Article (신문기사로부터 추출한 최근동향에 대한 트위터 감성분석)

  • Lee, Gyoung Ho;Lee, Kong Joo
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.10
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    • pp.731-738
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    • 2013
  • We analyze public opinion via a sentiment analysis of tweets collected by using recent topic keywords extracted from newspaper articles. Newspaper articles collected within a certain period of time are clustered by using K-means algorithm and topic keywords for each cluster are extracted by using term frequency. A sentiment analyzer learned by a machine learning method can classify tweets according to their polarity values. We have an assumption that tweets collected by using these topic keywords deal with the same topics as the newspaper articles mentioned if the tweets and the newspapers are generated around the same time. and we tried to verify the validity of this assumption.

A topic modeling analysis for Korean online newspapers: Focusing on the social perceptions of nurses during the COVID-19 epidemic period (토픽모델링을 이용한 한국 인터넷 뉴스의 간호사 관련 기사 분석: COVID-19 유행시기를 중점으로)

  • Chang, Soo Jung;Park, Sunah;Son, Yedong
    • The Journal of Korean Academic Society of Nursing Education
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    • v.28 no.4
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    • pp.444-455
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    • 2022
  • Purpose: This study explored the meaning of the social perceptions of nurses in online news articles during the coronavirus disease 2019 (COVID-19) pandemic. Methods: A total of 339 nurse-related articles published in Korean online newspapers from January 1 to December 31, 2020, were extracted by entering various combinations of OR and AND with the four words "Corona," "COVID," "Nursing," and "Nurse" as search keywords using BIGKinds, a news database provided by the Korea Press Foundation. The collected data were analyzed with a keyword network analysis and topic modeling using NetMiner 4. Results: The top keywords extracted from the nurse-related news articles were, in the following order, "metropolitan area," "protective clothing," "government," "task," and "admission." Four topics representing keywords were identified: "encouragement for dedicated nurses," "poor work environment," "front-line nurses working with obligation during the COVID-19 pandemic," and "nurses' efforts to prevent the spread of COVID-19." Conclusion: The media's attention to the dedication of nurses, the shortage of nursing resources, and the need for government support is encouraging in that it forms the public opinion necessary to lead to substantial improvements in treating nurses. The nursing community should actively promote policy proposals to improve treatment toward nurses by utilizing the net function of the media and proactively seek and apply strategies to improve the image of nurses working in various fields.

A Study on AI Evolution Trend based on Topic Frame Modeling (인공지능발달 토픽 프레임 연구 -계열화(seriation)와 통합화(skeumorph)의 사회구성주의 중심으로-)

  • Kweon, Sang-Hee;Cha, Hyeon-Ju
    • The Journal of the Korea Contents Association
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    • v.20 no.7
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    • pp.66-85
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    • 2020
  • The purpose of this study is to explain and predict trends the AI development process based on AI technology patents (total) and AI reporting frames in major newspapers. To that end, a summary of South Korean and U.S. technology patents filed over the past nine years and the AI (Artificial Intelligence) news text of major domestic newspapers were analyzed. In this study, Topic Modeling and Time Series Return Analysis using Big Data were used, and additional network agenda correlation and regression analysis techniques were used. First, the results of this study were confirmed in the order of artificial intelligence and algorithm 5G (hot AI technology) in the AI technical patent summary, and in the news report, AI industrial application and data analysis market application were confirmed in the order, indicating the trend of reporting on AI's social culture. Second, as a result of the time series regression analysis, the social and cultural use of AI and the start of industrial application were derived from the rising trend topics. The downward trend was centered on system and hardware technology. Third, QAP analysis using correlation and regression relationship showed a high correlation between AI technology patents and news reporting frames. Through this, AI technology patents and news reporting frames have tended to be socially constructed by the determinants of media discourse in AI development.

Topic Analysis Using Big Data Related to 'Blockchain usage': Focused on Newspaper Articles ('블록체인 활용' 관련 빅데이터를 활용한 토픽 분석: 신문기사를 중심으로)

  • Kim, Sungae;Jun, Soojin
    • Journal of Industrial Convergence
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    • v.18 no.1
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    • pp.73-78
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    • 2020
  • To analyze the main topics related to the use of blockchain technology, the Topic Modeling Technique was applied to the 'Blockchain Technology Utilization' big data shown in newspaper articles. To this end, from 2013 to 2019, when newspaper articles on the use of blockchain technology first appeared, the topics were extracted from 21 newspapers and analyzed by time to 15,537 articles. As a result of the analysis, articles related to the utilization of blockchain technology have increased exponentially since 2015 and focused on IT_science and economics. Key words related to cryptocurrency, bitcoin and virtual currency were weighted high, although they differed depending on time. Blockchain technology, which had focused on financial transactions, gradually expanded to big data, Internet of Things and artificial intelligence. As a result, changes in corporate topics were also made together to expand into various fields at banks for financial transactions, focusing on large and global companies. The study showed how these topics were changing, along with the main topics in newspaper articles related to the use of blockchain technology.

A Topic Analysis of Fine Particle Matter by Using Newspaper Articles (신문기사를 이용한 미세먼지 이슈의 토픽 분석)

  • Yang, Ji-Yeon
    • The Journal of the Korea Contents Association
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    • v.22 no.6
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    • pp.1-14
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    • 2022
  • This study aims to identify topics in newspaper articles related to fine particle matter and to investigate the characteristics and time series trend of each topic. Related national newspaper articles during 1990 and 2021 were collected from Bigkinds. A total of 18 topics have been discovered using LDA, and 11 clusters deduced from clustering. Hot topics include related products/residence, overseas cause(China), power plant as a domestic cause, nationwide emergency reduction measures, international cooperation, political issues, current situation & countermeasure in other countries, and consumption patterns. Cold topics include the concentration standard and indoor air quality improvement. These findings would be useful in inferring the political direction and strategies. In particular, the consumer protection policy should be expanded as the related market is growing. It will also be necessary to pursue policies that will promote public safety and health, and that will enhance public consensus and international cooperation.