• Title/Summary/Keyword: On-line News Analysis

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The Influences of On Line WOM(word Of Mouth) Information and Receiver's Characteristic on WOM Received (온라인 구전정보와 수신자 특성이 구전수용에 미치는 영향)

  • Kim, Chang-Ho
    • The Journal of Information Technology
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    • v.8 no.3
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    • pp.73-82
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    • 2005
  • The present paper aims to examine the relationship between the online word of mouth(WOM) contents and the WOM effect and to see how receivers' features such as product knowledge and involvement level influence the WOM received. For that purpose, we categorize WOM contents into two subcategories; product news and personal experience. The WOM effect, in turn, is into the WOM received. Survey questionnaires were given to 268 collegians as to their online WOM activities to purchase MP3 players. SPSS 10.0 package was employed as the method of statistical analysis. We report the following results. First, product news is shown to exert a greater effect on the WOM received than personal experience. Second, their product knowledge plays a moderating role in the relationship between the WOM contents and the WOM received. Finally, it is shown that the factor of involvement level moderates the relationship between the WOM contents and the WOM received. The current paper attempts to develop a hypothetical relationship between WOM information and WOM received and to provide a theoretical foundation for the practical online marketing. We must admit the methodological limitations with respect to subjects and samples. It should be worthwhile, however, to compare online and off-line marketing and to expand the range of research in the current line of thought.

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Analysis of the Types of News Stories on the Online Broadcast -Focusing upon the Broadcasting Websites of NAVER Newsstand- (온라인 방송의 뉴스기사 유형에 대한 분석 -네이버 뉴스스탠드의 방송사 홈페이지를 중심으로-)

  • Park, Kwang Soon
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.177-185
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    • 2021
  • This paper aimed to grasp what the percentage in the types of news stories on the online broadcast is, which was conducted by analyzing the news stories of 9 broadcasting websites on the Naver newsstand. For the analysis, a total of 270 days' samples were selected, including 30 days per broadcast on 9 broadcasting websites. For a method of analysis, One-way ANOVA was used to examine the difference among broadcasting websites. The analysis was made centering with priorities given to the type of news stories by the composition of language, the type of genre as a standard of stories, and so on. As a result of analysis, all the programs in the off-line broadcast have been produced and transmitted as a video-typed story, but a half of those in on-line broadcast have been made up of the stories composed of photo and text. The online newspaper has been producing a new type of news' story using video-typed story or computer graphic while the online broadcast has actively been utilizing stories composed of photos and text, which are types of newspaper's stories. From above-mentioned results, it can be understood that the boundary among media is getting more and more indistinct on the environment of online media, showing the phenomenon that the type of broadcast's stories is becoming old-fashioned.

Analysis of News Agenda Using Text mining and Semantic Network Analysis: Focused on COVID-19 Emotions (텍스트 마이닝과 의미 네트워크 분석을 활용한 뉴스 의제 분석: 코로나 19 관련 감정을 중심으로)

  • Yoo, So-yeon;Lim, Gyoo-gun
    • Journal of Intelligence and Information Systems
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    • v.27 no.1
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    • pp.47-64
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    • 2021
  • The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

An Analysis of the Comparative Importance of Systematic Attributes for Developing an Intelligent Online News Recommendation System: Focusing on the PWYW Payment Model (지능형 온라인 뉴스 추천시스템 개발을 위한 체계적 속성간 상대적 중요성 분석: PWYW 지불모델을 중심으로)

  • Lee, Hyoung-Joo;Chung, Nuree;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.75-100
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    • 2018
  • Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.

Comparative Analysis of Mainstream O1line News Use with Alternative Online News Use -In the Aspens of the Users' Characteristics, the Attitude on Online News Sites, and Using Pattern.- (주류 인터넷 언론과 대안 인터넷 언론의 이용 비교 -이용집단의 특성, 이용자의 뉴스사이트에 대한 태도 뉴스 이용 패턴-)

  • Park, Sun-Hee
    • Korean journal of communication and information
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    • v.26
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    • pp.259-289
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    • 2004
  • In this study, the use of mainstream online news site and alternative online news site were compared in the aspects of users' characteristics, attitude on online news sites, and using pattern. A survey was conducted for 182 mainstream-only users, 46 alternative online news users, and 47 both sites users, Also, their traffic data of online news sites were analyzed during the 16th presidential election. As a result, it was found that both sites users had the highest political interest and the most progressive political position among the user groups. In the aspect of users' attitude, mainstream-only users were most positive to the mainstream online news site and both sires users were most positive and more involved in alternative online news site. But all user groups set higher credibility on alternative online news site than mainstream online news sire. In the comparison of user size, mainstream online news site has larger user size than alternative online site. However, the user royalty, such as time per person, pages per person, and visiting days per person, was lower than that of the latter. These results suggest thar small but differentiated news sires have royal users, and online news users be segmented according to news contents.

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Crisis Management Analysis of Foot-and-Mouth Disease Using Multi-dimensional Data Cube (다차원 데이터 큐브 모델을 이용한 구제역의 위기 대응 방안 분석)

  • Noh, Byeongjoon;Lee, Jonguk;Park, Daihee;Chung, Yongwha
    • The Journal of the Korea Contents Association
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    • v.17 no.5
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    • pp.565-573
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    • 2017
  • The ex-post evaluation of governmental crisis management is an important issues since it is necessary to prepare for the future disasters and becomes the cornerstone of our success as well. In this paper, we propose a data cube model with data mining techniques for the analysis of governmental crisis management strategies and ripple effects of foot-and-mouth(FMD) disease using the online news articles. Based on the construction of the data cube model, a multidimensional FMD analysis is performed using on line analytical processing operations (OLAP) to assess the temporal perspectives of the spread of the disease with varying levels of abstraction. Furthermore, the proposed analysis model provides useful information that generates the causal relationship between crisis response actions and its social ripple effects of FMD outbreaks by applying association rule mining. We confirmed the feasibility and applicability of the proposed FMD analysis model by implementing and applying an analysis system to FMD outbreaks from July 2010 to December 2011 in South Korea.

An Analysis on the Newspaper's Layout of the News Stand in NAVER -Focusing on the Websites of 10 dependent Online Newspapers (네이버 뉴스스탠드의 신문지면에 대한 비교분석 -10개 종속형 온라인 신문의 홈페이지를 중심으로)

  • Park, Kwang Soon
    • Journal of Digital Convergence
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    • v.16 no.9
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    • pp.365-374
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    • 2018
  • This study aims at understanding the components of on-line newspaper and how each newspaper's layout configuration is differentiated through the analysis on the websites of 10 general daily newspapers in the news stand of NAVER. The collection of data was implemented twice, and One-Way ANOVA was used as an analyzing way. The content of the analysis was carried out based on the types of visual images, the number of photo-based articles and title-based articles, the size of image for the main story, etc. As a result of analysis, the rate of news articles with the audios, videos, cards and slides differentiated from paper-based newspaper was low, and also the news articles using the informative graphics and the graphic sources were very small in number. As a whole, the newspapers in the news stand of NAVER showed that they attempt to make a distinction of their newspaper layout by using a variety of editorial techniques. The significance of this paper is to offer a basic clue to the editing formation to promote the news consumption of newspapers. Under the circumstance that the ecology of media is rapidly being reformed by new media technology, the continuous study of how the newspaper layout should be changed will be needed.

Use of the 20th Presidential Election Issues on YouTube: A Case Study of 'Daejang-dong Development Project' (유튜브 이용자의 제20대 대통령선거 이슈 이용: '대장동 개발 사업' 사례를 중심으로)

  • Kim, Chunsik;Hong, Juhyun
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.4
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    • pp.435-444
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    • 2022
  • There are three focuses in the paper. Firstly, the study identified what channels were most viewed by YouTube users to watch the 'Daejang-dong scandal,' which was the most powerful agenda to influence the candidate preference among voters during the 20th presidential election. Secondly, the study analyzed whether the political tone of the first videos was in line with that of the subsequent videos. Finally, we compared the sentiment of comments on the first and subsequent videos. The results showed that TBS 'News Factory' and 'TV Chosun News' represented liberal and conservative factions, respectively. Secondly, the political tone of channels that were viewed subsequently was neutral, but the conservative channel users left more negative comments and that was significant statistically. In addition, about 80% of the conservative and liberal channel users shared the same political tendency with the channel they watched first, and more than 90% of the comments left at the subsequent videos in line with that of at the first news. Based on these results, the study concluded that the voters tended to seek political news that was similar with their political ideology, and it was considered a sort of echo chamber phenomenon on the YouTube. The study suggests that the performance of high-quality journalism by traditional news outlet might contribute to decrease the negative influence of political contents on YouTube users.

Multimodal Approach for Summarizing and Indexing News Video

  • Kim, Jae-Gon;Chang, Hyun-Sung;Kim, Young-Tae;Kang, Kyeong-Ok;Kim, Mun-Churl;Kim, Jin-Woong;Kim, Hyung-Myung
    • ETRI Journal
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    • v.24 no.1
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    • pp.1-11
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    • 2002
  • A video summary abstracts the gist from an entire video and also enables efficient access to the desired content. In this paper, we propose a novel method for summarizing news video based on multimodal analysis of the content. The proposed method exploits the closed caption data to locate semantically meaningful highlights in a news video and speech signals in an audio stream to align the closed caption data with the video in a time-line. Then, the detected highlights are described using MPEG-7 Summarization Description Scheme, which allows efficient browsing of the content through such functionalities as multi-level abstracts and navigation guidance. Multimodal search and retrieval are also within the proposed framework. By indexing synchronized closed caption data, the video clips are searchable by inputting a text query. Intensive experiments with prototypical systems are presented to demonstrate the validity and reliability of the proposed method in real applications.

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