• Title/Summary/Keyword: 뉴스주제

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Research on the Composition and Diversity Changes of the Main News Programs' News Topic at the Initial Introduction of General Programming Cable Channels (종편 출범 초기의 지상파와 종편 메인뉴스의 주제 구성 및 다양성 변화에 대한 연구)

  • Yoo, Soojung
    • The Journal of the Korea Contents Association
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    • v.18 no.10
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    • pp.53-64
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    • 2018
  • This study analyzed contents of main news of 7 channels for 4 years during the initial period of introduction of the general programming cable channel(GPCC) in order to examine changes in subject composition and diversity of broadcasting news contents due to the introduction of GPCC. As a result of the analysis, terrestrial broadcasters treated a wide range of topics, while the GPCC's news focused on political news and differentiated from the terrestrial in the composition of the topic. In the composition of the news topic headline news, GPCC showed distinctive structure using political news and North Korea news, while terrestrial news was treated as major news for economic and daily information news. As a result of analyzing the diversity of broadcast news in the first four years of opening GPCC, it has changed into a strategy of selecting and concentrating in order to compete with the terrestrial broadcasters. In the initial broadcasting news market, the terrestrial broadcastings were used to maintain diversity strategies while the GPCCs were using concentrated strategies.

An Analysis of News Report Characteristics on Archives & Records Management for the Press in Korea: Based on 1999~2018 News Big Data (뉴스 빅데이터를 이용한 우리나라 언론의 기록관리 분야 보도 특성 분석: 1999~2018 뉴스를 중심으로)

  • Han, Seunghee
    • Journal of the Korean Society for information Management
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    • v.35 no.3
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    • pp.41-75
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    • 2018
  • The purpose of this study is to analyze the characteristics of Korean media on the topic of archives & records management based on time-series analysis. In this study, from January, 1999 to June, 2018, 4,680 news articles on archives & records management topics were extracted from BigKinds. In order to examine the characteristics of the media coverage on the archives & records management topic, this study was analyzed to the difference of the press coverage by period, subject, and type of the media. In addition, this study was conducted word-frequency based content analysis and semantic network analysis to investigate the content characteristics of media on the subject. Based on these results, this study was analyzed to the differences of media coverage by period, subject, and type of media. As a result, the news in the field of records management showed that there was a difference in the amount of news coverage and news contents by period, subject, and type of media. The amount of news coverage began to increase after the Presidential Records Management Act was enacted in 2007, and the largest amount of news was reported in 2013. Daily newspapers and financial newspapers reported the largest amount of news. As a result of analyzing news reports, during the first 10 years after 1999, news topics were formed around the issues arising from the application and diffusion process of the concept of archives & records management. However, since the enactment of the Presidential Records Management Act, archives & records management has become a major factor in political and social issues, and a large amount of political and social news has been reported.

Examining News Report Research Trends Using Keyword Network Analyses (국내 뉴스 보도 연구 동향에 관한 주제어 연결망 분석)

  • Cho, Yiyoung;Ahn, Dohyun
    • The Journal of the Korea Contents Association
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    • v.16 no.8
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    • pp.278-291
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    • 2016
  • This study examined research trends via network analyses of keywords appeared in academic research articles about news reports in South Korea during the last 10 years from 2006 to 2015. Keyword network analyses of 4410 keywords from 1108 articles suggested that framing, agenda setting, third-person effect, selective exposure, and uses and gratification were main theories but most studies used framing theory. Research areas included news reports on politics, economics, science, world issues, or tour. However, research on news reports covering culture, sports or daily life were not identified. In terms of media, research on both traditional and emerging media were ample. Research on broadcasting new, online news, and social media were frequently observed.

A Study on the Establishment and Applications of the "News Core Thesaurus" ("뉴스 코어 시소러스"의 구축 및 활용 방안에 관한 연구)

  • Chang, Inho
    • Journal of Korean Library and Information Science Society
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    • v.44 no.3
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    • pp.489-512
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    • 2013
  • This study suggests the establishment and applications of the News core thesaurus for efficient indexing and searching of news information. News core thesaurus was constructed as macrothesauri which can cover all of news subjects and then has microthesauri like politics, economy, society, culture, etc. as its subsets. In this research, News core thesaurus embodied 2,012 descriptors and 74 non-descriptors by SKOS(Simple Knowledge Organization System). It suggests measures that treat only special subjects in detail in weekly newspaper or biweekly newspaper with little information and special subjects, which is not daily newspaper, and use each microthesauri by merging or integrating in huge news archives or portal sites.

Time Analysis of Structural Element and Theme Association of Television News Imagery (텔레비전 뉴스 영상의 구조적 요소와 주제연관성 시계열 분석)

  • Park, Dug-Chun
    • The Journal of the Korea Contents Association
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    • v.11 no.7
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    • pp.100-109
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    • 2011
  • This thesis is a content analysis on whether the proportion of structural element and theme association of television news imagery is different, depending on the historical background, and on what it means, which can be the index of scene-based and realistic report. Most researches of television news are horizontal studies of the same period, making light of vertical studies reflecting the change of age. Therefore, This study analyzed 729 items composed of 11,945 shots extracted from MBC Newsdesk from 1987, to 2007, the samples of which were extracted by systematic random sampling with five years' interval. This content analysis found out that there was high proportion of scene-based and realistic report such as 'sound-bite', 'event footage', 'direct matching' in the year 1987, 2007, and high proportion of 'corroboration shot', 'file footage', 'indirect reference', 'literal matching only' in the year 1997, which revealed the fact that reality-based report had not been faithfully accomplished in 1997.

Research on Multi-facted News Article Classification Models Classifying Subjects, Geographies and Genres (심층 주제, 지역, 장르를 모두 분류할 수 있는 다면적 뉴스 기사 자동 분류 모델 연구)

  • Hyojin Lee;SungPil Choi
    • Journal of the Korean Society for Library and Information Science
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    • v.58 no.3
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    • pp.65-89
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    • 2024
  • This study developed a model to classify news articles into categories of topic, genre, and region using a Korean Pre-trained Language model. To achieve this, a new news article classification system was designed by referring to the classification systems of domestic media outlets. The topic and genre classification models were implemented as hierarchical classification models that link the main categories and subcategories, and their performance was compared with that of an integrated category model. The evaluation results showed that the hierarchical structure classification model had the advantage of providing more precise categorization in ambiguous or overlapping categories compared to the integrated category model. For regional classification of news articles, a model was built to classify into 18 categories, and for regional news articles, the regional characteristics were clearly reflected in the text, resulting in high performance. This study demonstrated the effectiveness of classifying news articles from multiple perspectives-topic, genre, and region-and emphasized the significance of suggesting the potential for a multi-dimensional news article classification service that meets user needs.

Article Analytic and Summarizing Algorithm by facilitating TF-IDF based on k-means (TF-IDF를 활용한 k-means 기반의 효율적인 대용량 기사 처리 및 요약 알고리즘)

  • Jang, Minseo;OH, Sujin;Kim, Ung-Mo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.05a
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    • pp.271-274
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    • 2018
  • 본 논문에서는 뉴스기사 데이터를 활용하여 대규모 뉴스기사를 소주제로 분류하는 군집 분석 방법을 제안한다. 또한, 분류된 뉴스기사를 사용자가 빠르게 이해하고 접할 수 있도록 핵심 문장을 추출하여 제공하는 방법을 제안한다. 분석 데이터는 포털 사이트 점유율 1위인 네이버의 경제 분야 뉴스기사를 크롤링하여 수집한다. 뉴스기사의 분석을 위해 전 처리를 통해 특수문자, 조사, 어미, 구두점 등의 불 용어 처리를 수행한다. 또한, k-means 알고리즘을 이용하여 대용량의 뉴스기사를 주제 별로 분류하는 것을 진행하며 그것을 토대로 핵심 문장을 추출한다. 추출된 핵심 문장은 분류된 뉴스기사의 주제를 나타내며 사용자에게 빠르게 정보를 전달하기 위해 활용한다. 본 논문의 연구 내용이 여러 언론사 사이트에 반영되면 사이트 품질과 사용자 만족도 향상에 기여할 수 있을 것으로 보인다.

Usability Test to Improve the News Applications of the Major Broadcasting Companies :Focus on the MBC and SBS (지상파 방송사의 뉴스 앱 개선을 위한 사용성 평가 :MBC와 SBS를 중심으로)

  • Oh, Ryeong;Lim, Soon-Bum
    • The Journal of the Korea Contents Association
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    • v.21 no.3
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    • pp.10-22
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    • 2021
  • This study conducted usability test to users in 20s in order to find problems for improving news apps of the major broadcasting companies. Efficiency, effectiveness, and satisfaction were evaluated by mobile news content type. Also there is including analysis of the news topics (hard news, soft news) and broadcasters (MBC, SBS). As a result, same problems were found in common items according to mobile news content types. And in the news topic, there was a difference in the news values and news attributes that need to be improved. This study gives practical implications to the news producers to improve the contents of news apps.

Identifying Seoul city issues based on topic modeling of news article (토픽 모델링 기반 뉴스기사 분석을 통한 서울시 이슈 도출)

  • Kwon, Min-Ji
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2019.11a
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    • pp.11-13
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    • 2019
  • 대중들에게 정보를 빠르고 정확하게 제공하는 대표 매체인 뉴스 기사는 일 평균 1만 5천 건 이상이 보도되고 있다. 특정 주제 또는 분야에 대한 전반적인 동향을 파악하고자 대량의 텍스트 데이터를 수집하여 텍스트 마이닝(Text mining)과 머신러닝 등을 적용하는 연구들이 활발하게 수행되고 있다. 본 연구에서는 서울시의 이슈 및 문제를 파악하고자 약 5년간 뉴스 기사를 수집하여 키워드 분석 및 토픽 모델링을 적용하였다. 분석 결과 5년간의 뉴스 기사에서 빈번하게 출현하는 키워드들을 도출하였고 연도별로 도출된 키워드들을 비교분석하였다. 또한 토픽 모델링 적용 결과 뉴스 기사를 구성하는 20개의 주제를 도출하였으며 이를 기반으로 서울시의 주요 이슈들을 파악할 수 있다. 본 연구는 연도별, 분야별 세부 내용 및 시계열 분석, 다른 도시들의 이슈 및 문제를 도출하는데 활용될 것으로 기대된다.

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Document Embedding and Image Content Analysis for Improving News Clustering System (뉴스 클러스터링 개선을 위한 문서 임베딩 및 이미지 분석 자질의 활용)

  • Kim, Siyeon;Kim, Sang-Bum
    • Annual Conference on Human and Language Technology
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    • 2015.10a
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    • pp.104-108
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    • 2015
  • 많은 양의 뉴스가 생성됨에 따라 이를 효과적으로 정리하는 기법이 최근 활발히 연구되어왔다. 그 중 뉴스클러스터링은 두 뉴스가 동일사건을 다루는지를 판정하는 분류기의 성능에 의존적인데, 대부분의 경우 BoW(Bag-of-Words)기반 벡터유사도를 사용하고 있다. 본 논문에서는 BoW기반의 벡터유사도 뿐 아니라 두 문서에 포함된 사진들의 유사성 및 주제의 관련성을 측정, 이를 분류기의 자질로 추가하여 두 뉴스가 동일사건을 다루는지 판정하는 분류기의 성능을 개선하는 방법을 제안한다. 사진들의 유사성 및 주제의 관련성은 최근 각광을 받는 딥러닝기반 CNN과 신경망기반 문서임베딩을 통해 측정하였다. 실험결과 기존의 BoW기반 벡터유사도에 의한 분류기의 성능에 비해 제안하는 두 자질을 사용하였을 경우 3.4%의 성능 향상을 보여주었다.

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