• Title/Summary/Keyword: News Data

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Fake News Detection on Social Media using Video Information: Focused on YouTube (영상정보를 활용한 소셜 미디어상에서의 가짜 뉴스 탐지: 유튜브를 중심으로)

  • Chang, Yoon Ho;Choi, Byoung Gu
    • The Journal of Information Systems
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    • v.32 no.2
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    • pp.87-108
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    • 2023
  • Purpose The main purpose of this study is to improve fake news detection performance by using video information to overcome the limitations of extant text- and image-oriented studies that do not reflect the latest news consumption trend. Design/methodology/approach This study collected video clips and related information including news scripts, speakers' facial expression, and video metadata from YouTube to develop fake news detection model. Based on the collected data, seven combinations of related information (i.e. scripts, video metadata, facial expression, scripts and video metadata, scripts and facial expression, and scripts, video metadata, and facial expression) were used as an input for taining and evaluation. The input data was analyzed using six models such as support vector machine and deep neural network. The area under the curve(AUC) was used to evaluate the performance of classification model. Findings The results showed that the ACU and accuracy values of three features combination (scripts, video metadata, and facial expression) were the highest in logistic regression, naïve bayes, and deep neural network models. This result implied that the fake news detection could be improved by using video information(video metadata and facial expression). Sample size of this study was relatively small. The generalizablity of the results would be enhanced with a larger sample size.

A Study on Fake News Subject Matter, Presentation Elements, Tools of Detection, and Social Media Platforms in India

  • Kanozia, Rubal;Arya, Ritu;Singh, Satwinder;Narula, Sumit;Ganghariya, Garima
    • Asian Journal for Public Opinion Research
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    • v.9 no.1
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    • pp.48-82
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    • 2021
  • This research article attempts to understand the current situation of fake news on social media in India. The study focused on four characteristics of fake news based on four research questions: subject matter, presentation elements of fake news, debunking tool(s) or technique(s) used, and the social media site on which the fake news story was shared. A systematic sampling method was used to select a sample of 90 debunked fake news stories from two Indian fact-checking websites, Alt News and Factly, from December 2019 to February 2020. A content analysis of the four characteristics of fake news stories was carefully analyzed, classified, coded, and presented. The results show that most of the fake news stories were related to politics in India. The majority of the fake news was shared via a video with text in which narrative was changed to mislead users. For the largest number of debunked fake news stories, information from official or primary sources, such as reports, data, statements, announcements, or updates were used to debunk false claims.

News Data Analysis Using Acoustic Model Output of Continuous Speech Recognition (연속음성인식의 음향모델 출력을 이용한 뉴스 데이터 분석)

  • Lee, Kyong-Rok
    • The Journal of the Korea Contents Association
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    • v.6 no.10
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    • pp.9-16
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    • 2006
  • In this paper, the acoustic model output of CSR(Continuous Speech Recognition) was used to analyze news data News database used in this experiment was consisted of 2,093 articles. Due to the low efficiency of language model, conventional Korean CSR is not appropriate to the analysis of news data. This problem could be handled successfully by introducing post-processing work of recognition result of acoustic model. The acoustic model more robust than language model in Korean environment. The result of post-processing work was made into KIF(Keyword information file). When threshold of acoustic model's output level was 100, 86.9% of whole target morpheme was included in post-processing result. At the same condition, applying length information based normalization, 81.25% of whole target morpheme was recognized. The purpose of normalization was to compensate long-length morpheme. According to experiment result, 75.13% of whole target morpheme was recognized KIF(314MB) had been produced from original news data(5,040MB). The decrease rate of absolute information met was approximately 93.8%.

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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.

A Study of Effect of SNS News Consumption on Social Engagement and Government Transparency in Cambodia

  • Chhaya, PhalPheaktra;Cho, Wan-Sup;Kwon, Sun-Dong
    • Journal of Information Technology Applications and Management
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    • v.22 no.3
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    • pp.19-33
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    • 2015
  • SNS is perceived as an effective tool for sharing news and enabling news content to reach many more users than before. And some users think that SNS is an important source to get news. This study's purpose is to understand the key factors contributing to behavior of news consumption on social network sites in Cambodia and its influence. We identified three key factors including convenience, recency, and variety; however, recency showed less significant effect on news consumption on SNS. Besides the key factors, it also seeks to understand the impact of news consumption on social engagement and government's transparency in Cambodia. The analytical results achieved through the Partial Least Squares (PLS) approach.

The Impacts of the COVID-19 Pandemic on the Movement of Composite Stock Price Index in Indonesia

  • ZAINURI, Zainuri;VIPHINDRARTIN, Sebastiana;WILANTARI, Regina Niken
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.3
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    • pp.1113-1119
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    • 2021
  • This study aims to determine the impact of the news coverage of the COVID-19 pandemic on the composite stocks' movement (IHSG) in Indonesia. This study used secondary data of daily time series with an observation range of March 2020-June 2020. This study used three main variables, namely, COVID-19 news, the daily price of a composite stock market index (IHSG), and interest rate. This study clarifies pandemic news into two forms to facilitate quantitative analysis, namely, good news and bad news. Both pandemic news conditions, which have been clarified, are then processed into the index and reprocessed along with two other variables using vector autoregressive (VAR). The results showed that the good news have a dominant effect on developing the composite stock price index (IHSG) in Indonesia during the COVID-19 pandemic. Although the good news dominates the composite stock price index (IHSG) movement in Indonesia, the bad news must also be anticipated. By implementing a series of macroeconomic policies that follow the conditions of the composite stock price index (IHSG) movements on the stock exchange floor, the bad news response can decrease the potential for a decline in investor confidence, so that the financial system's macroeconomic stability is maintained.

ChungbukN: An User Location based News Retrieval System (충북N:사용자 위치 기반 뉴스 검색 시스템)

  • Kwon, Sun-Ock;Jeong, Ji-Seong;Kim, Ji-Hoon;Kim, Hee-Ran;Yoo, Kwan-Hee
    • The Journal of the Korea Contents Association
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    • v.12 no.12
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    • pp.524-532
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    • 2012
  • According to increasing in number of smart phone subscribers to offer the convenience of users, wide range of applications in various fields have emerged. Recently, a lot of applications are being developed to provide a way of receiving information according to the user's current location. Also, the news seems difficult to provide the necessary information among the numerous data. Especially, it is difficult to find the news that associated with the region. There are many applications that provide news, but there is no system to provide news information according to the user's location information in domestic, so users not receive the news of the region. In this paper, we propose a news retrieval application which provides users with news around by using the location information of smart phone users. Because this system provides news of the region, it has the advantage to obtain the around information easily. The proposed system, whose name is 'ChungbukN', provides news that receives data at chungbuk comprehensive daily newspaper 'Daily Chungbuk'.

Development of a Fake News Detection Model Using Text Mining and Deep Learning Algorithms (텍스트 마이닝과 딥러닝 알고리즘을 이용한 가짜 뉴스 탐지 모델 개발)

  • Dong-Hoon Lim;Gunwoo Kim;Keunho Choi
    • Information Systems Review
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    • v.23 no.4
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    • pp.127-146
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    • 2021
  • Fake news isexpanded and reproduced rapidly regardless of their authenticity by the characteristics of modern society, called the information age. Assuming that 1% of all news are fake news, the amount of economic costs is reported to about 30 trillion Korean won. This shows that the fake news isvery important social and economic issue. Therefore, this study aims to develop an automated detection model to quickly and accurately verify the authenticity of the news. To this end, this study crawled the news data whose authenticity is verified, and developed fake news prediction models using word embedding (Word2Vec, Fasttext) and deep learning algorithms (LSTM, BiLSTM). Experimental results show that the prediction model using BiLSTM with Word2Vec achieved the best accuracy of 84%.

COVID-19 News Analysis Using News Big Data : Focusing on Topic Modeling Analysis (뉴스 빅데이터를 활용한 코로나19 언론보도 분석 :토픽모델링 분석을 중심으로)

  • Kim, Tae-Jong
    • The Journal of the Korea Contents Association
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    • v.20 no.5
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    • pp.457-466
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    • 2020
  • The purpose of this study is to find out what the main agenda of social formation is and how it changes through the media by utilizing the news big data of COVID-19 which is spreading recently, and to suggest the direction of future reporting. In order to achieve the purpose of the research, 47,816 cases of news big data reported from December 31, 2019 to March 11, 2020 were divided into four periods based on the fourth stage of the crisis warning for infectious diseases, and a total of 20 topics were derived. Based on the results of the Topic Modeling analysis, this study proposed the following. First, it is necessary to refrain from provocative expressions such as "anxiety" and "fear" and use neutral and objective reporting terms. Second, more in-depth and contextual news production is required, breaking away from simple event news production. Third, it is necessary to prepare detailed crisis communication manuals for each situation related to infectious diseases. Fourth, we need reports that focus on citizens-led efforts to overcome the crisis. This research has the academic significance that it is the first paper to analyze news big data on COVID-19 using the Topic Modeling Analysis method, and the policy significance that can be used as the basis for developing national crisis communication policy.

A Trend Analysis of Changes in Housework due to Technological Innovation and Family Change

  • LEE, Hyun-Ah;KWON, Soonbum
    • East Asian Journal of Business Economics (EAJBE)
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    • v.10 no.1
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    • pp.109-121
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    • 2022
  • Purpose - This study attempted to analyze news big data in order to examine the trend of change in housework due to technological innovation and family changes. Research design, data, and methodology - News big data was collected from Bigkinds for the purpose of trend analysis. A total of 8,270 articles containing 'housework' were extracted from news articles between January 1, 1990 and December 31, 2021. 11 general daily newspapers and 8 business newspapers were selected and were analyzed by dividing them into five-year units. Result - The change of trends in housework that appeared through news big data analysis can be summarized as below. First, the tendency to regard housework as work of women or housewives is gradually weakening. Instead, the centrality of connection with double income is increasing. Second, there is a tendency to strengthen the institutional approach to evaluation of the productivity of housework. Third, the possibility of market substitution for housework is expanding. Conclusion - In the era of the 4th industrial revolution, examining the impact of technological innovation and family change on housework not only enables the prospect of an industry, but also provides implications for policies related to housework. In addition, this study is differentiated in that it contributed to expand the field of housework research previously limited to analyzing survey data.