• Title/Summary/Keyword: news frequency

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A Big Data Analysis of the News Trends on Wireless Emergency Alert Service (뉴스 빅데이터를 활용한 재난문자 뉴스 게재 경향 분석)

  • Lee, Hyunji;Byun, Yoonkwan;Chang, Sekchin;Choi, Seong Jong;Oh, Seunghee;Lee, Yongtae
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.726-734
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    • 2019
  • This study investigates the number of news and correlated keywords concerning to Korean Wireless Emergency Alert(KWEA). The news was collected using BIGKinds, a news big data system provided by the Korea Press Foundation. When analyzing the annual published news articles, we investigated the frequency of the news grouped by disaster types, and the frequency of the news distinguishing between the earthquake and non-earthquake disasters, and finally the frequency of correlated keywords concerning to the disasters. We found that the KWEA news totaled 182 in 2016 due to the unprecedented powerful KyongJu earthquake, an increase of 20 times over the previous year. Ever since 2016, the news about the KWEA continued to hit high figures consistently. After the peak in KyongJu earthquake in 2016, the proportion of non-earthquakes had also increased in 2017 and 2018. Next, the keyword correlation analysis showed that the KWEA news gave major coverage to the following entities: The Ministry of the Interior and Safety which operates the KWEA, Korea Meteorological Administration, and the general public.

Effects of Anchors' Reputation and Brand Equity Evaluation of TV News Program on the Continuous Watching Intention : Focusing on KBS, JTBC, YTN TV News (TV 뉴스 프로그램의 앵커 평판과 브랜드 자산 평가가 지속적 시청 의도에 미치는 영향 : KBS, JTBC, YTN 뉴스를 중심으로)

  • Ha, Dong-Keun;Ahn, Seo-Jin
    • The Journal of the Korea Contents Association
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    • v.18 no.9
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    • pp.91-101
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    • 2018
  • This research verified the effects of anchors' reputation and brand equity evaluation of news on the continuous watching intention for general news channels such as KBS, JTBC, and YTN. Data collection was conducted on nationwide 539 adults who were watching news for each channel, and Hierarchical regression analysis was conducted to analyze the impact of the anchors' reputation and news brand equity evaluation factors. As a result, first, KBS showed continuous watching intention as viewers are men, their academic background is lower, they are more conservative, viewing frequency is higher, anchor awareness is higher, and news awareness and news preference are higher. Second, JTBC showed continuous watching intention as viewers are more advancing, viewing frequency is higher, anchor confidence, news awareness, and news preference, and evaluation on news quality are higher. Third, YTN showed continuous watching intention as their viewing frequency is higher, anchor confidence and anchor attraction are higher, news preference and evaluation on news quality are higher.

Antecedents of News Consumers' Perceived Information Overload and News Consumption Pattern in the USA

  • Lee, Sun Kyong;Kim, Kyun Soo;Koh, Joon
    • International Journal of Contents
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    • v.12 no.3
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    • pp.1-11
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    • 2016
  • This exploratory study examines the critical factors associated with news consumers' perception of information overload and news consumption patterns. An online survey was conducted with Qualtrics panels (N = 1001). The demographics and three antecedent factors of perceived information overload were considered including the frequency of news access through multiple media platforms, level of attention to news, and interest in news. Three news consumption patterns were investigated as possible consequences of perceived information overload: news avoidance, selective exposure, and willingness to pay for news. The results of hierarchical regression analyses revealed a meaningful distinction between general and news information overload. Overall, news consumers who paid more attention to news through newer media/platforms/devices perceived higher levels of information overload, were more willing to pay for the news, and often avoided news or selectively exposed themselves to certain sources of news to manage news information overload.

Kakao Deep Reading Index: Consumption Time as a Key Factor in News Curation Algorithm

  • Lee, Dongkwon;Kim, Daewon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.10
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    • pp.4833-4848
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    • 2019
  • This paper introduces the structure and effects of Kakao's news curation algorithm, which is created based on the Deep Reading Index (DRI). The DRI examines the extent of deep reading through content reading time, that is, the duration of reader engagement with an article. Current news curation algorithms focus on reader choice, with the click-through rate or pageviews as the gauge for consumption frequency. DRI is a product of the challenge of introducing and adopting a new factor called 'consumption time' instead of 'frequency of consumption', which is the basis of existing curation algorithms. The analysis of DRI-based services proves that the new algorithm can act as a curation system that is more effective in providing in-depth and quality news reports.

An Innovative Approach of Bangla Text Summarization by Introducing Pronoun Replacement and Improved Sentence Ranking

  • Haque, Md. Majharul;Pervin, Suraiya;Begum, Zerina
    • Journal of Information Processing Systems
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    • v.13 no.4
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    • pp.752-777
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    • 2017
  • This paper proposes an automatic method to summarize Bangla news document. In the proposed approach, pronoun replacement is accomplished for the first time to minimize the dangling pronoun from summary. After replacing pronoun, sentences are ranked using term frequency, sentence frequency, numerical figures and title words. If two sentences have at least 60% cosine similarity, the frequency of the larger sentence is increased, and the smaller sentence is removed to eliminate redundancy. Moreover, the first sentence is included in summary always if it contains any title word. In Bangla text, numerical figures can be presented both in words and digits with a variety of forms. All these forms are identified to assess the importance of sentences. We have used the rule-based system in this approach with hidden Markov model and Markov chain model. To explore the rules, we have analyzed 3,000 Bangla news documents and studied some Bangla grammar books. A series of experiments are performed on 200 Bangla news documents and 600 summaries (3 summaries are for each document). The evaluation results demonstrate the effectiveness of the proposed technique over the four latest methods.

Analysis of Drone Technology Using in Journalism : Focusing on Log and Diary of Korean General Service Program Provider (드론기술의 저널리즘 활용 실태 : 종합편성채널 방송 활용 일지 분석을 중심으로)

  • Lim, Hyunchan
    • Journal of Korea Multimedia Society
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    • v.23 no.4
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    • pp.588-594
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    • 2020
  • This study analyzes the current status of drone journalism in Korean broadcasting industry, with a case study of TV Chosun Company's drone use for news gathering. It analyzes TV Chosun's record of drone logs between 2014 and 2018. The log consists of date, time, news content, users, machine and on-air date. In 2014, the total of 31 cases of using drones for news gathering is identified, while in 2018, the frequency increases to 60, with a gradual, annual increase, making the total frequency of 160, during the period between 2014 and 2018. This means that the broadcasting company used the drone news gathering system every week. The analysis also reveals that the company used this drone news gathering system mostly in the metropolitan area in Korea, amounting to more than 76 per cent of its total use: 31.3 per cent in Seoul, 36.9 per cent in Kyunggi, and 8.1 percent in Incheon. The system was more frequently used in the summer and autumn than the winter and spring. Interestingly, it was first popularly used for disaster related news, but the use of drone for social and other issues is increasing every year, which may imply its diverse use in the future.

Analyzing Quotations in News Reporting from Western Foreign Press: Focusing on Evaluative Language

  • Ban, Hyun;Noh, Bokyung
    • International Journal of Advanced Culture Technology
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    • v.4 no.3
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    • pp.62-68
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    • 2016
  • This study explores evaluative linguistic expressions in news reporting about the 2016 general election outcome in Korean newspapers. In particular, we have examined the evaluative linguistic expressions quoted from the three Western news media -New York Times, Washington Post, and BBC, both quantitatively and qualitatively in Korean news stories in order to know how journalists frame the news stories to persuade news consumers to accept their ideologies. This is based on the assumption that quotation can be a tool in conveying ideologies to news consumers (van Dijk, 1988, Jullian, 2011). To achieve this purpose, we selected ten Korean newspapers which included quotations from the news stories of the three Western media and then analyzed the quoted expressions quantitatively and qualitatively. For a qualitative analysis, evaluative linguistic expressions were analyzed to examine the journalistic stances of the Western news stories, following Martin's (2003) appraisal theory. For a quantitative analysis, a word frequency analysis was conducted to figure out the ratio of quoted words to the whole news texts in Korean newspapers. As a result, it was found that the news stories of BBC and Washington Post were more frequently quoted than that of New York Times when journalists conveyed neutral or positive attitude to the election outcome, thus confirming that evaluative linguistic expressions were functionally employed to convey journalists' ideologies or stances to news readers.

PMCN: Combining PDF-modified Similarity and Complex Network in Multi-document Summarization

  • Tu, Yi-Ning;Hsu, Wei-Tse
    • International Journal of Knowledge Content Development & Technology
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    • v.9 no.3
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    • pp.23-41
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    • 2019
  • This study combines the concept of degree centrality in complex network with the Term Frequency $^*$ Proportional Document Frequency ($TF^*PDF$) algorithm; the combined method, called PMCN (PDF-Modified similarity and Complex Network), constructs relationship networks among sentences for writing news summaries. The PMCN method is a multi-document summarization extension of the ideas of Bun and Ishizuka (2002), who first published the $TF^*PDF$ algorithm for detecting hot topics. In their $TF^*PDF$ algorithm, Bun and Ishizuka defined the publisher of a news item as its channel. If the PDF weight of a term is higher than the weights of other terms, then the term is hotter than the other terms. However, this study attempts to develop summaries for news items. Because the $TF^*PDF$ algorithm summarizes daily news, PMCN replaces the concept of "channel" with "the date of the news event", and uses the resulting chronicle ordering for a multi-document summarization algorithm, of which the F-measure scores were 0.042 and 0.051 higher than LexRank for the famous d30001t and d30003t tasks, respectively.

Covid 19 News Data Analysis and Visualization

  • Hur, Tai-Sung;Hwang, In-Yong
    • Journal of the Korea Society of Computer and Information
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    • v.27 no.4
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    • pp.37-43
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    • 2022
  • In this paper, we calculate the word frequency by date and region using news data related to COVID-19 distributed for about 8 months from December 2019 to July 2020, and visualized the correlation with the current state data of COVID-19 patients using the results. News data was collected from Big Kids, a news big data system operated by the Korea Press Promotion Foundation. The visualization system proposed in this paper shows the news frequency of the selected region compared to the overall region, the key keyword of the selected region, the region of the main keyword, and the date change of the selected region. Through this visualization, the main keywords and trends of COVID-19 confirmed and infected people can be identified for previous events.

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.