• The Journal of the Acoustical Society of Korea
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• v.26 no.3E
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• pp.74-79
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• 2007

In this paper, we report our recent work on a indexing and retrieval system of broadcast news using audio content analysis. Key issues addressed in this work are two major parts of the audio indexing system: anchorperson detection based on audio segmentation, and phone-based spoken document retrieval, developed in the framework of the emerging MPEG-7 standard. Experiments are conducted on a database of Britisch broadcast news videos. We discuss the development of the retrieval system, and the evaluation of each part and the retrieval system.

• Asian Journal for Public Opinion Research
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• v.8 no.2
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• pp.67-104
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• 2020

Fake news and disinformation provoked heated arguments during Taiwan's 2018 local election. Most significantly, concerns grew that Beijing was attempting to sway the island's politics armed with a new "Russian-style influence campaign" weapon (Horton, 2018). To investigate the speculated effects of the "onslaught of misinformation," an online survey with 1068 randomly selected voters was conducted immediately after the election. Findings confirmed that false news affected Taiwanese voters' judgment of the news and their voting decisions. More than 50% of the voters cast their votes without knowing the correct campaign news. In particular, politically neutral voters, who were the least able to discern fake news, tended to vote for the China-friendly Kuomintang (KMT) candidates. Demographic analysis further revealed that female voters tended to be more likely to believe fake news during the election period compared to male voters. Younger or lower-income voters had the lowest levels of discernment of fake news. Further analyses and the implications of these findings for international societies are deliberated in the conclusion.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.3 no.2
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• pp.239-243
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• 2003

Recently, there has been active research conducted on the intelligent agent in various fields. The results have been widely applied to intelligent user-friendly interfaces. In this system, we modeled, designed, and implemented an intelligent agent system that can be applied to stock and news. Some procedures such as login sequence to the web site, process to get stock information, setting stock in concern, intelligent news system module, news analysis module, and news learning module are modeled in detail and described in block diagram level. In our experiment on stock system, it showed quite a useful alarming screen avatar result and also on news system. it successfully rearranged the order of the news according to the user's preferences.

• Knowledge Management Research
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• v.14 no.4
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• pp.1-17
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• 2013

As online communities proliferate, online news sites have received great attention in news media research. Although most of the online news sites provide contents for free, some have adopted the Pay-What-You-Want (PWYW) model by offering a voluntary payment option to the readers. In this study, we investigate the factors which influence subscribers' voluntary payment behavior on an online news site. Drawing upon both the Stimulus-Organism-Response (SOR) framework and the Elaboration Likelihood Model (ELM), we hypothesize that appreciation has a direct effect on the subscribers' voluntary payment behavior, whereas central factors (positive emotional content, cognitive content) and peripheral factors (news sharing, news article length) of the news articles have indirect impacts on voluntary payment behavior through the enhanced appreciation. Based on an empirical analysis of 172 news articles from the Korean online news site that adopted the PWYW pricing model (i.e., Ohmynews.com), we find that appreciation plays a critical role in voluntary payment behavior and that peripheral factors have significant impacts on appreciation. However, the impacts of central factors on appreciation are not found. By identifying influencing factors of subscribers' voluntary payment behavior on online news sites for the first time, this paper suggests a prospective alternative profit model for online news providers faced with fierce competition.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.143-150
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• 2019

This study aimed to analyze the keyword related to Health Disparity in Korea through the method of keyword network analysis and to establish a basic database for suggesting ideas for prospective studies in physical education. To achieve the goal, this study crawled co-occured keyword with 'health' and 'disparity' from news casted in 20 different channels. The duration of the news was 3 months, from September 11th, 2018 to December 11th. The results are as follows. First, among the news during recent 3 months, there were 1,383 keyword related to health disparity and this study selected 173 keyword which had co-occured over 3 times. Second, the inclusiveness of the network was 97.674% and the density was .038. Third, analyzing news related to health disparity, 'mortality' was the most co-occured keyword and 'disparity', 'reinforcement', 'the most', 'health', '6 times', 'Seoul', 'half', 'medicine', and 'local' were shown similarly. And common keyword in 4 centrality were 13 keyword. Lastly, by analyzing eigenvector centrality, significantly different result has shown. 'Disparity' was the most co-occured keyword. Based on this result, this study showed the necessity for reinforcing the public physical education in public education system in Korea. In order to achieve it, the field of physical education must look beyond present elite-focused physical education to public physical activity.

• 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.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.141-148
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• 2019

In this study, the Technology Acceptance Model (TAM) was applied to explore the process of using card news. Card news users are found to be active in searching and selecting appropriate news for themselves, information seeking style and news literacy were established as antecedent variables that can influence card news usage. A survey of 400 university students with experience of using card news was conducted. For statistical analysis, SEM was conducted. The analysis showed that information seeking style significantly affects perceived ease of use (PEU) and that news literacy influences neither PEU nor PU. PEU was found to have a significant effect on PU, and both PEU and PU had a significant effect on recommendation intention.

• Journal of Industrial Convergence
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• v.20 no.12
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• pp.135-143
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• 2022

This paper aims to grasp what propensity users have in their ideology from the comments in the Web Portal News and the Press Website News. Through these analytical results, the political propensities of not only the Web Portal News and the Press Website News but also the voters who use these news media could be grasped. The collection of data necessary for this study has been made from the comments of 174 news stories for about 90 days before the election day. For the analysis, T-test has been used in order to compare Naver News with Daum News, the Minjoo Party of Korea with the People Power Party, and the Press Web Site News with Naver News. As a result of the analysis, the comments of Naver News took the higher percentage in the positive writings about the candidates of the conservative party. but, in contrast, those of Daum News in that percentage were higher about the ones of the progressive party. Accordingly, it can be found that Naver News is mainly used by users with the politically conservative propensity, while Daum News is mostly used by those with progressive one.

• 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.