• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.89-103
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• 2023

The purpose of this study is to investigate the mediating effect of news literacy in the relationship between sense of community and political efficacy. This study conducted a survey targeting the MZ generation. The survey was conducted online, and data from 309 cases were used for analysis. The research results are as follows. As a result of correlation analysis between sense of community, political efficacy, and news literacy, it was found that there was a statistically significant correlation between sense of community and news literacy sub factors. Second, the relationship between sense of community and political efficacy was found to have a significant positive effect on political efficacy as sense of community increased. Third, the relationship between sense of community and news literacy was confirmed to have a significant positive effect on news literacy as sense of community increased. Fourth, regarding the relationship between news literacy and political efficacy, it was confirmed that news literacy has a significant effect on political efficacy. Fifth, in the relationship between sense of community and political efficacy, news literacy was found to mediate the relationship between sense of community and political efficacy of the MZ generation. Based on the research results, news literacy education is required from the perspective of civic education, and differentiated educational contents by age are proposed.

• Journal of Korea Technology Innovation Society
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• v.19 no.1
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• pp.80-104
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• 2016

Existing methodologies of technology planning about promising new technology focused on target technology itself, so it is true that socio-environmental context which the relevant technology has influence on is not well understood. In this respect, this study is aimed to questingly examine that news content analysis methodologies widely available in the field of science communication can be applied as a complementary methodology for contextual understanding of socio-environment in terms of technology planning about promising new technology. In the co-evolutionary environment of technology-society, promising new technology shows hype phenomenon regarding the relation with the society. Based on this, this study performed news content analysis and examined if the consequences of analysis would match hype cycle. It tried to explore substantive content understanding by socio-environment factors according to specific news frame content. To do this, new content analysis was performed targeting cloud computing as a representative promising new technology. The result of news content analysis targeting general newspapers, business news, IT special newspapers revealed that the tendency of news reporting matched the trend of hype cycle. Particularly, it was verified that reporting attitude and news frame analysis provided useful information to understand contextual content depending on social, economic, and cultural environment factors about promising new technology. The results of this study implied that news content analysis could overcome the limitation of technology information analysis focusing on academic journal patent usually applied for technology planning and could be used as a complementary methodology for understanding the context depending on macro-environment factors. In conclusion, application of news content analysis on the phase of macro-environment analysis of technology planning could contribute to the securement of mutually balanced view in the co-evolutionary perspective of technology-society.

• Asia pacific journal of information systems
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• v.32 no.4
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• pp.945-963
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• 2022

With the widespread use of social media, online social platforms like Twitter have become a place of rapid dissemination of information-both accurate and inaccurate. After the COVID-19 outbreak, the overabundance of fake information and rumours on online social platforms about the COVID-19 pandemic has spread over society as quickly as the virus itself. As a result, fake news poses a significant threat to effective virus response by negatively affecting people's willingness to follow the proper public health guidelines and protocols, which makes it important to identify fake information from online platforms for the public interest. In this research, we introduce an approach to detect fake news using deep learning techniques, which outperform traditional machine learning techniques with a 93.1% accuracy. We then investigate the content differences between real and fake news by applying topic modeling and linguistic analysis. Our results show that topics on Politics and Government services are most common in fake news. In addition, we found that fake news has lower analytic and authenticity scores than real news. With the findings, we discuss important academic and practical implications of the study.

• 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.

• Journal of Information Technology Applications and Management
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• v.25 no.1
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• pp.19-32
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• 2018

Fake news is defined as the news articles that are intentionally and verifiably false, and could mislead readers. Spread of fake news may provoke anxiety, chaos, fear, or irrational decisions of the public. Thus, detecting fake news and preventing its spread has become very important issue in our society. However, due to the huge amount of fake news produced every day, it is almost impossible to identify it by a human. Under this context, researchers have tried to develop automated fake news detection method using Artificial Intelligence techniques over the past years. But, unfortunately, there have been no prior studies proposed an automated fake news detection method for Korean news. In this study, we aim to detect Korean fake news using text mining and machine learning techniques. Our proposed method consists of two steps. In the first step, the news contents to be analyzed is convert to quantified values using various text mining techniques (Topic Modeling, TF-IDF, and so on). After that, in step 2, classifiers are trained using the values produced in step 1. As the classifiers, machine learning techniques such as multiple discriminant analysis, case based reasoning, artificial neural networks, and support vector machine can be applied. To validate the effectiveness of the proposed method, we collected 200 Korean news from Seoul National University's FactCheck (http://factcheck.snu.ac.kr). which provides with detailed analysis reports from about 20 media outlets and links to source documents for each case. Using this dataset, we will identify which text features are important as well as which classifiers are effective in detecting Korean fake news.

• Korean Management Science Review
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• v.31 no.4
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• pp.93-106
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• 2014

This paper investigated customers' willingness to pay (WTP) for the integrated news platform, which is a paid digital news service provided by Korean newspapers. The integrated news platform has been widely employed and regarded as an alternative to recover dramatically decreasing sales of newspapers since N-Screen era began. This study employed a conjoint analysis to examine WTP for the integrated news platform and its attributes. According to the results, WPT for the integrated news platform was estimated as 4543.6 won, which is only 30.3% of the real price. Digitalized newspaper and premium news were found to be significant attributes explaining customers' WTP. The results of this paper implies that present marketing strategies for the integrated news platform of Korean newspapers should be reconsidered and revised.

• International Journal of Advanced Culture Technology
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• v.11 no.2
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• pp.36-43
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• 2023

This study aims to derive discourse's linguistic meaning, production method, and social practice implications by analyzing news reports on de-facility for people with disabilities. To this end, the discourse was analyzed by applying Fairclough's framework of critical discourse analysis. The subject of analysis is a news article on the de-facility of the disabled on the N portal site, and the analysis period is one year, from January 1 to December 31, 2022. First, as a result of the study, the surface meaning of the news discourse on the de-facility for disabled people was ideological through the seriousness of the problem for disabled people, the poor environment, and the policy of de-facility for disabled people separated from reality. Second, the social meaning of the de-facility news discourse for disabled people appeared from a realistic perspective, such as the structural cause of the problem for disabled people and the need for sensible government policies and measures to practice de-facility for disabled people. Finally, the socio-cultural practical implications of the de-facility news discourse for people with disabilities proposed the development of a systematic and realistic de-facility management manual for the disabled, practical government policy support, and changes in self-support perception for disabled people. The results of this study are expected to help find an alternative direction to reduce the gap between actual policies for de-facility for disabled people and practice in the field in the future.

• Informatization Policy
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• v.19 no.3
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• pp.19-35
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• 2012

As Internet users increasingly consume news through the Internet, Internet portals face criticism that they are quickening the softening of public news and molding public opinions. Some portals have started to provide newscast services that directly connect the press, not grouping news sources on their own standards. This study aims to clarify how news grouping models and newscast models are different in terms of news softening and agenda setting. Specifically, authors conduct a content analysis on time-specific news content provided by top three portals-Naver, Daum, and Nate. By doing so, this study examines characteristics of news service models of Internet portals and their social and political implications. According to our study, the softening and tabloidization of portal news had not been improved even after adopting the newscast model. Therefore, portal journalism should be reorganized as a way to circulate healthy and qualified news content.

• Korean journal of communication and information
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• v.81
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• pp.225-271
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• 2017

What is the basic nature of Korean public broadcasting system? This research explores this question through an analysis of KBS news coverage of the Korean housing market. This study spotlights the internal news production processes. In detail, this study investigates newsroom routines, such as news selection, news gatherings, and news production. As a result, this study reveals KBS can be classified as "Publicity Model" following reasons. First, KBS news selection process stresses higher viewer ratings for competitive market share and belittles public interests of serving the citizen. This caused KBS news to provide fragmented and truncated news information and to constrict high quality news of significant information for citizen. Second, KBS newsroom operates under the minimum staff resource to produce news programmes and has developed official source dependency as a routine for news gathering. Third, under the limits of report format, KBS news worked as a neutral deliverer of government message and failed to provide more detailed information and diverse viewpoints.

• Journal of Information Technology Applications and Management
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• v.26 no.6
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• pp.1-12
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• 2019

On the Internet age, the news is generated and distributed not only by traditional news media, but also by a variety of online news media, news platforms, content websites/content farms, and social media. Since it is an easy task to create and distribute news, some of these news reports may contain fake or false facts. In the end, the cyberspace is full of fake or false messages. People may wonder if these fake news actually influence our decision making. In this paper, we discussed a real case of fake news. In this case, a Taiwanese company used some fake news, advertorial news, and news placement to manipulate or influence its stock price and trade volume. We collected all news for the case company during a period of four years and five months (from January 2013 to May 2017). We analyzed the relationship between published news and stock price. Based on the analysis results, we conclude that we should not ignore the influence of news placement and fake business news on the stock price.