• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.105-117
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• 2021

This study examined the factors that influence the emotional expression in comments on the hot news about the 'Restaurant Collapse in Linfen City, Shanxi Province' published in Sina Weibo.. As a result of the study, first, there were differences in emotional expression according to gender. Women expressed stronger anger, disappointment, sadness, and condemnation than men. Second, the intensity of emotional expression of users in the eastern region was significantly higher than that of users in the central and western region. Third, the greater the number of Weibo, the total number of blogs where users participated in comments and posted emotional expressions, the stronger the emotional expression was. Fourth, unauthenticated users showed stronger emotional expressions of disappointment and sadness than authenticated users. The results of this study present implications for the factors influencing emotional expression on hot news. This study is meaningful in that it can be compared with social networks such as Twitter and Facebook in the West by looking at the factors that influence emotional expression in the process of online public opinion formation in China, and also meaningful in that a big data analysis method was used in online news analysis.

• Asian Journal for Public Opinion Research
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• v.8 no.4
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• pp.432-452
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• 2020

This study explored the representation of risks from the controversial Lynas rare earth refining as a risk event by five Malaysian online mainstream and alternative newspapers using qualitative content analysis. The aim is to uncover the role of the news media in the social amplification and attenuation of risks within the literature evidence as those roles are still uncertain. Content analysis is used to explore the online newspapers' roles guided by the Social Amplification of Risk Framework (SARF). The representations typified environmental, financial, health, occupational, property, radioactive, and technological risks and established connections between four risk types (environmental, financial, radioactive, and health risks). Radioactive risk was repeatedly associated with other risks, suggesting that the volume and information flow focused on radioactive risk as a key ingredient for amplification. This connection shows that the nature of the relationship between risks is multidimensional, contradicting the unidirectional type found in previous studies. Alternative online newspapers amplified and attenuated more risks, thus, providing more diverse coverage than mainstream sources. Consequently, this study provides evidence that risk representation from rare earth refining in a digital news environment is multidimensional and intensified or weakened in a multi-layered pattern. The stakeholders are engaged in a contestation by positioning their narratives to oppose or support their interests, which are amplified or attenuated by the online newspapers as social amplification stations.

• Journal of Contemporary Eastern Asia
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• v.18 no.2
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• pp.16-32
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• 2019

Media manipulation of breaking news through article selection, ranking and tweaking of social media data and comment streams is a growing concern for society. We argue that the combination of human and machine curation on media portals marks a new period for news media and journalism. Although intermediary platforms routinely claim that they are merely the neutral technological platform which facilitates news and information flows, rejecting any criticisms that they are operating as de facto media organisations; instead, we argue for an alternative, more active interpretation of their roles. In this article we provide a contemporary account of the South Korean ('Korean') online news media ecology as an exemplar of how contemporary media technologies, and in particular portals and algorithmic recommender systems, perform a powerful role in shaping the kind of news and information that citizens access. By highlighting the key stakeholders and their positions within the production, publication and distribution of news media, we argue that the overall impact of the major portal platforms of Naver and Kakao is far more consequential than simply providing an entertaining media diet for consumers. These portals are central in designing how and which news is sourced, produced and then accessed by Korean citizens. From a regulatory perspective the provision of news on the portals can be a somewhat ambiguous and moving target, subject to soft and harder regulatory measures. While we investigate a specific case study of the South Korean experience, we also trace out connections with the larger global media ecology. We have relied on policy documents, stakeholder interviews and portal user 'walk throughs' to understand the changing role of news and its surfacing on a distinctive breed of media platforms.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.483-497
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• 2020

We used a deep neural network model for the prediction of the stock prices of Kia Motors and Shinsegae as listed in the KOSPI 100. We used an emotional variable derived from online news in addition to the various technical indicators most often used. The emotional variable used as a predictor variable was generated from the average of the emotional scores for companies in the industrial group after building an emotional dictionary specific to each industrial group classified in a social network analysis. The study was conducted with various combinations of predictors and confirmed that good predictive and profitable power could be expected when jointly using technical indicators and an emotional variable based on online news by industrial groups.

• Journal of Digital Convergence
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• v.17 no.9
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• pp.399-406
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• 2019

The purpose of this study is to examine the relationship between corporate reputation and the profitability. In this study, Big Data Analysis was conducted for Hyundai Motor, Shinsegae Department Store, SK Telecom, and Amorepacific to solve research problems. The results of this study show that the effect of each corporate reputation on the profitability is different according to the company. For products such as Hyundai Motor and Amorepacific that are used directly by consumers, the corporate reputation formed by the comments was more influential. In addition, distribution Service company such as Shinsegae Department Store showed more influence by online news. On the other hand, SK Telecom did not have a significant effect on profitability. Based on the results, this study emphasizes the importance of online news and comments on corporate reputation management, and aims to contribute to establishing an efficient reputation management strategy by examining the relationship between corporate reputation and profitability.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.71-85
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• 2004

Many online content providers who use the Internet to distribute contents, such as news, music, games, books, and other types of information, have been experiencing an extremely competitive business environment. To survive in this environment, they have started charging a fee for the contents that they provide. However, there have been very few success stories in commercializing online contents. One of the biggest hurdles may be customers' psychological resistance against paying a fee for the contents that have been free of charge previously. Without examining customers' perceived prices for online contents, many online content providers have tended to decide their prices by themselves. Online games are not exceptional cases. Although many online game-related research works have focused on psychological and technical aspects, very few works have examined online garners' preference carefully. This study alms at exploring online garners' preference by measuring their WTP (willingness to pay) for online games.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.569-578
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• 2021

Thanks to web development today, we can easily access online news via various media. As much as it is easy to access online news, we often face fake news pretending to be true. As fake news items have become a global problem, fact-checking services are provided domestically, too. However, these are based on expert-based manual detection, and research to provide technologies that automate the detection of fake news is being actively conducted. As for the existing research, detection is made available based on contextual characteristics of an article and the comparison of a title and the main article. However, there is a limit to such an attempt making detection difficult when manipulation precision has become high. Therefore, this study suggests using a verifying article to decide whether a news item is genuine or not to be affected by article manipulation. Also, to improve the precision of fake news detection, the study added a process to summarize a subject article and a verifying article through the summarization model. In order to verify the suggested algorithm, this study conducted verification for summarization method of documents, verification for search method of verification articles, and verification for the precision of fake news detection in the finally suggested algorithm. The algorithm suggested in this study can be helpful to identify the truth of an article before it is applied to media sources and made available online via various media sources.

• ETRI Journal
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• v.33 no.5
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• pp.741-751
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• 2011

This paper focuses on online speaker tracking for telephone conversations and broadcast news. Since the online applicability imposes some limitations on the tracking strategy, such as data insufficiency, a reliable approach should be applied to compensate for this shortage. In this framework, a set of reference speaker models are used as side information to facilitate online tracking. To improve the indexing accuracy, adaptation approaches in eigenvoice decomposition space are proposed in this paper. We believe that the eigenvoice adaptation techniques would help to embed the speaker space in the models and hence enrich the generality of the selected speaker models. Also, an index structure of the reference models is proposed to speed up the search in the model space. The proposed framework is evaluated on 2002 Rich Transcription Broadcast News and Conversational Telephone Speech corpus as well as a synthetic dataset. The indexing errors of the proposed framework on telephone conversations, broadcast news, and synthetic dataset are 8.77%, 9.36%, and 12.4%, respectively. Using the index tree structure approach, the run time of the proposed framework is improved by 22%.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.173-187
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• 2012

As newspapers which have been major news media are being replaced by on-line news media in recent years, many researchers are paying attention to "comments(news users' short remarks on an article)", a newly emerged way of forming public opinion. This study is examining how the similarity between political disposition of on-line news visitors and that of news media impacts upon their evaluation on quality of comments from the viewpoint of 'social identity theory.' This study may have academic significance because it inspected the pattern of media usage and the cognition of comments in relation to political disposition for the first time and showed 'comments reading' and the function of comments to form public opinion(comments journalism).

• Journal of Korean Academy of Nursing
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• v.47 no.6
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• pp.806-816
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• 2017

Purpose: As comprehensive nursing care service has gradually expanded, it has become necessary to explore the various opinions about it. The purpose of this study is to explore the large amount of text data regarding comprehensive nursing care service extracted from online news and social media by applying a semantic network analysis. Methods: The web pages of the Korean Nurses Association (KNA) News, major daily newspapers, and Twitter were crawled by searching the keyword 'comprehensive nursing care service' using Python. A morphological analysis was performed using KoNLPy. Nodes on a 'comprehensive nursing care service' cluster were selected, and frequency, edge weight, and degree centrality were calculated and visualized with Gephi for the semantic network. Results: A total of 536 news pages and 464 tweets were analyzed. In the KNA News and major daily newspapers, 'nursing workforce' and 'nursing service' were highly rated in frequency, edge weight, and degree centrality. On Twitter, the most frequent nodes were 'National Health Insurance Service' and 'comprehensive nursing care service hospital.' The nodes with the highest edge weight were 'national health insurance,' 'wards without caregiver presence,' and 'caregiving costs.' 'National Health Insurance Service' was highest in degree centrality. Conclusion: This study provides an example of how to use atypical big data for a nursing issue through semantic network analysis to explore diverse perspectives surrounding the nursing community through various media sources. Applying semantic network analysis to online big data to gather information regarding various nursing issues would help to explore opinions for formulating and implementing nursing policies.