• Journal of Information Science Theory and Practice
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• v.10 no.2
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• pp.1-16
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• 2022

This study aimed to understand young adults' attitudes concerning news and news resources they consumed, and how they encounter the fake news phenomenon. A qualitative approach was used with semi-structured interviews with 41 young adults (aged 20-30) in Tehran, Iran. Findings revealed that about half of the participants favored social media, and a smaller group used traditional media and only a few maintained that traditional and modern media should be used together. News quality was considered to be lower on social media than in traditional news sources. Furthermore, young adults usually followed the news related to the issues which had impact on their daily life, and they typically tended to share news. To detect fake news, they checked several media to compare the information; and profiteering and attracting audiences' attention were the most important reasons for the existence of fake news. This is the first qualitative study for understanding news consumption behavior of young adults in a politicized society.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.197-216
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• 2022

With the development of Internet and mobile technology and the spread of social media, a large amount of information is being generated and distributed online. Some of them are useful information for the public, but others are misleading information. The misleading information, so-called 'fake news', has been causing great harm to our society in recent years. Since the global spread of COVID-19 in 2020, much of fake news has been distributed online. Unlike other fake news, fake news related to COVID-19 can threaten people's health and even their lives. Therefore, intelligent technology that automatically detects and prevents fake news related to COVID-19 is a meaningful research topic to improve social health. Fake news related to COVID-19 has spread rapidly through social media, however, there have been few studies in Korea that proposed intelligent fake news detection using the information about how the fake news spreads through social media. Under this background, we propose a novel model that uses Graph2vec, one of the graph embedding methods, to effectively detect fake news related to COVID-19. The mainstream approaches of fake news detection have focused on news content, i.e., characteristics of the text, but the proposed model in this study can exploit information transmission relationships in social engagement networks when detecting fake news related to COVID-19. Experiments using a real-world data set have shown that our proposed model outperforms traditional models from the perspectives of prediction accuracy.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.83-90
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• 2015

This paper examines the rising value of social networked journalism and analyzes the case of a social news site based on the theory of networked journalism. Social networked journalism allows the public to be involved in every aspect of journalism production through crowd-sourcing and interactivity. The networking effect with the public is driving journalism to transform into a more open, more networked and more responsive venue. "wikitree" is a social networking news service on which anybody can write news and disseminate it via Facebook and Twitter. It is operated as an open sourced program which incorporates "Google Translate" to automatically convert all its content, enabling any global citizen with an Internet access to contribute news production and share either their own creative contents or generated contents from other sources. Since its inception, "wikitree global" site has been expanding its coverage rapidly with access points arising from 160 countries. Analyzing its international coverage by country and by news category as well as by the unique visit numbers via SNS, the results of the case study imply that networking with the global public can enhance news traffic to the social news site as well as to specific news items. The results also suggest that the utilization of Twitter and Facebook in social networked journalism can break the boundary between local and global public by extending news-gathering ability while growing audience's interest in the site, and engender a feasible business model for a local online journalism.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.309-318
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• 2017

This study is for analyzing the tone, the frame and the characteristics of political news in social media. Social news media is not same as old media in sharing news freely by SNS like tweeter, facebook and reporting, editing by anyone using SNS with various opinions. With Content analysis, sampling 419 cases from 'Wikitree' by the keyword, 'presidential election', all the full text analysed each how is social media making public opinion differently and which frame is using in. As the result, the social media has different tone, frame, and characteristic due to the reported figure, type of report, information source, attitude to the government, specifically shows a lack of in-depth report and distinct soft-journalism just same as old media's. Because the tone of social news media is not probable, specific but improbable, vague, using the irrational, strategic and episodic frame mainly.

• Journal of Information Science Theory and Practice
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• v.7 no.2
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• pp.40-53
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• 2019

Although fake news has been present in human history at any time, nowadays, with social media, deceptive information has a stronger effect on society than before. This article answers two research questions, namely (1) Is the dissemination of fake news supported by machines through the automatic construction of filter bubbles, and (2) Are echo chambers of fake news manmade, and if yes, what are the information behavior patterns of those individuals reacting to fake news? We discuss the role of filter bubbles by analyzing social media's ranking and results' presentation algorithms. To understand the roles of individuals in the process of making and cultivating echo chambers, we empirically study the effects of fake news on the information behavior of the audience, while working with a case study, applying quantitative and qualitative content analysis of online comments and replies (on a blog and on Reddit). Indeed, we found hints on filter bubbles; however, they are fed by the users' information behavior and only amplify users' behavioral patterns. Reading fake news and eventually drafting a comment or a reply may be the result of users' selective exposure to information leading to a confirmation bias; i.e. users prefer news (including fake news) fitting their pre-existing opinions. However, it is not possible to explain all information behavior patterns following fake news with the theory of selective exposure, but with a variety of further individual cognitive structures, such as non-argumentative or off-topic behavior, denial, moral outrage, meta-comments, insults, satire, and creation of a new rumor.

• Knowledge Management Research
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• v.20 no.2
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• pp.87-103
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• 2019

The purpose of this study was to explore the factors influencing acceptance (e.g., comprehension,) and diffusion of information recipients' by depending on the authenticity of news. Specifically, this study has examined the effects of the news contents(political vs. general), need for cognition(high vs. low) and authenticity of the News(real news vs. fake news) on both acceptance and diffusion of news. Based on previous work, this study has developed a conceptual model to present each research hypothesis and tested it by conducting experiments as the follows. As a result, according to the authenticity of the news and the contents of the news (political and general), the acceptance of political contents was high regardless of the authenticity of the news, and the acceptance of real news was higher than that of fake news. However, in the proliferation (comment), both the political contents and the general contents showed the characteristic of spreading (commenting) fake news rather than real news. contrary to this, the cognitive level did not show any significant difference in acceptance (understanding) and proliferation (comment, sharing, recommendation). This study provides academic implications in that it examines the influences of accepting (comprehension) and diffusion (comment, sharing, recommendation) of real news and fake news. It also provides practical implications for responding to fake news and new marketing strategies in an environment where contents are delivered through diverse social media.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.3
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• pp.173-183
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• 2019

This study aims to utilize big data contents of news and social media for developing a corporate strategy of multinational enterprises and their global decision-making through the data mining technique, especially text mining. In this paper, the data of 2 news media (BBC and CNN) and 2 social media (Facebook and Twitter) were collected for the three global leading Korean companies (Samsung, Hyundai Motor Company, and LG) from April, 2018 to April, 2019. The findings of this paper have shown that traditional news media and also modern social media have become devastating tools to extract global trends or phenomena for businesses. Moreover, this presents that a company can adopt a two-track strategy through two different types of media by deriving the key issues or trends from news media channels and also grasping consumers' sentiments, preference or issues of interest such as battery or design from social media. In addition, analyzing the texts of those media and understanding the association rules greatly contribute to the comparison between two different types of media channels to see the difference. Lastly, this provides meaningful and valuable data empowered insights to find a future direction comprehensively and develop a global strategy for sustainability of business.

• International Journal of Computer Science & Network Security
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• v.22 no.11
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• pp.348-356
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• 2022

The main objective of this paper is to probe the extent to which misinformation propagated through the different social media platforms contribute effectively in the process of directing, shaping and reshaping societal awareness of Saudis. In so doing, this paper attempts to delve into the relationship between linguistic misinformation and societal awareness, by exploring the perception of Saudis towards social media news, particularly misinformation and the extent to which this misinformation influences the social attitudes of Saudis in terms of various societal issues. Two main research questions are addressed in this study. First, to what extent does social media misinformation affect Saudis' awareness? Second, what are the linguistic manifestations of misinformation presented in the different social platforms? Two main findings have been recorded in this study: first, misinformation significantly contributes to the societal awareness of Saudis; and, second, however misinformation is linguistically manifested at the different levels of linguistic analysis, it is highly representative at the lexicalization level of language use.

• 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 Digital Contents Society
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• v.12 no.4
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• pp.475-483
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• 2011

This study examines how television news constructed an issue of social conflict between nationwide and local broadcasting. Especially, this study focused on new ariport of east-south region in Korea. To do this, this study conducted frame analysis on KBS, MBC, SBS main news including national and local ones, broadcasted from 1 January, 2011 to 15 April, 2011. In addition, frame analysis was divided into two aspects, formal and substance. As a result, the findings are as follow: First, in formal aspect both national and local broadcastings are dealing with episode style news frames, while subject style is just 7.5%. Second, in substance aspect, 6 categories are founded: site decision frame, competition and conflict frame, economic frame, rescission and response frame, government countermeasure and alternative frame, etc frame. In conclusion, national and local broadcasting television news have different perspective each other on defining an issues of social conflict like east-south new airport.