• The Journal of Information Systems
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• v.33 no.1
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• pp.159-182
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• 2024

Purpose This study aims to investigate the factors influencing social media users' sharing behaviors of COVID-19 health information. Specifically, we seek to examine the impact of three key antecedents-trust in information source, trust in information content, and trust in social media platform-on users' trust in information quality and determine whether their effects vary between South Korea and China. Design/methodology/approach To fulfill our research objectives, we conducted an online survey across two countries, collecting 408 valid responses (South Korea: N = 201; China: N = 207) for our analysis. We employed Partial Least Squared based Structural Equation Modeling (PLS-SEM) with SmartPLS 4 and performed Exploratory Factor Analysis (EFA) and independent t-tests with SPSS 27. Findings The study revealed that perceived risks significantly inhibit users from sharing health information, highlighting the critical role of trust in countering these effects. We also identified variances in the levels of trust in information content and trust in social media platform between the two countries, which offers fresh perspectives for designing culturally tailored public health communications and interventions.

• The Journal of Information Systems
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• v.32 no.4
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• pp.163-188
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• 2023

Purpose The study examines the impact of the level of anthropomorphism (both in appearance and behavior) of virtual humans on user liking. It investigates whether this relationship is mediated by social comparison experiences, with the moderated mediation effect of users' desire for self-improvement. Design/methodology/approach A between-groups experimental design was employed to examine the impact of different levels of appearance(low/mid/high) and behavior(low/high) anthropomorphism on user liking of virtual humans. The experiment was conducted in an online environment, and participants were randomly exposed to one of six stimuli, which were Instagram-like posts. Findings The results indicate that as virtual humans become more anthropomorphic, they have a positive impact on user liking. However, once the level of anthropomorphism in appearance reaches a certain point (mid vs high), there is no significant difference in user liking. Users who perceive virtual humans as highly anthropomorphic tend to engage in more social comparison experiences, which positively affects their liking for these virtual humans. Conversely, individuals with a high desire for self-improvement found that the positive effect of appearance anthropomorphism on liking through social comparison experiences was reduced. The study extends the application of social comparison theory by examining its impact on influencer marketing with virtual beings. It provides valuable insights for the formulation of influencer marketing strategies using virtual humans.

• International Journal of Contents
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• v.13 no.1
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• pp.62-67
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• 2017

This study attempts to explain how communication technology impacts global creative trends. We explore global creative trends based on award-winning creative topics presented at the 2016 Cannes Lions International Festival of Creativity. After analyzing award-winning topics, five main creative trends were selected with the keywords: technology, story-telling, social media, causes, and humor. The 2016 Cannes Lions Festival demonstrated that technology (i.e., virtual reality, artificial intelligence) has expanded the limits of creativity. Story-telling is still considered to be effective for raising audience attention. Social media enhances consumer engagement while nurturing future consumer relationships. Supporting social causes allows companies to garner goodwill from the public. Humor is powerful when it appropriately appeals to both products and customers.

• Asia Marketing Journal
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• v.26 no.2
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• pp.129-144
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• 2024

This research is on how people's trust in human-like AI-based service will influence customer engagement (CE). This study will discuss the relationship between trust and CE and explore how people's trust in AI affects CE when they lack knowledge of the company/brand. Items from the philosophical study of trust were extracted to build a scale suitable for trust in AI. The scale's reliability was ensured, and six components of trust in AI were merged into three dimensions: trust based on Quality Assurance, Risk-taking, and Corporate Social Responsibility. Trust based on quality assurance and risk-taking is verified to positively impact customer engagement, and the feelings about AI-based service fully mediate between all three dimensions of trust in AI and CE. The new trust scale for human-like AI-based services on social media sheds light on further research. The relationship between trust in AI and CE provides a theoretical basis for subsequent research.

• Knowledge Management Research
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• v.22 no.4
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• pp.41-70
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• 2021

The use of social media has many advantages such as knowledge sharing, social networking, and communicating with other people. However, it has given rise to various side effects including stress, Which is defined as social network stress in this study. This study aims to conceptualize social network stress and investigate its effect on switching behavior in social media. For this purpose, we present a research model that consists of the antecedents and consequences of social network stress and test it empirically using LISREL 8.7 based on the structural equation model. The empirical results showed that knowledge sharing and self-disclosure had positive impact on social network stress, which in turn positively influenced social media switching behaviors. In conclusion, we discussed both theoretical and practical implications of this research and suggested its limitations.

• Journal of the Korean Society of Safety
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• v.32 no.3
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• pp.83-89
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• 2017

A new technology has provided the nation, industry, society, and people with innovative and useful functions. National economy and society has been improved through this technology innovation. Despite the benefit of technology innovation, however, since technology society was sufficiently mature, the unintended side effect and negative impact of new technology on society and human beings has been highlighted. Thus, it is important to investigate a risk of new technology for the future society. Recently, the risks of the new technology are being suggested through a large amount of social data such as news articles and report contents. These data can be used as effective sources for quantitatively and systematically forecasting social risks of new technology. In this respect, this paper aims to propose a data-driven process for forecasting and assessing social risks of future new technology using the text mining, 4M(Man, Machine, Media, and Management) framework, and analytic hierarchy process (AHP). First, social risk factors are forecasted based on social risk keywords extracted by the text mining of documents containing social risk information of new technology. Second, the social risk keywords are classified into the 4M causes to identify the degree of risk causes. Finally, the AHP is applied to assess impact of social risk factors and 4M causes based on social risk keywords. The proposed approach is helpful for technology engineers, safety managers, and policy makers to consider social risks of new technology and their impact.

• Journal of Information Technology Services
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• v.14 no.1
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• pp.263-276
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• 2015

As a social being, people can cooperate and control one another through the power of reputation, which is a critical opinion of someone given by others. Nevertheless, there have been obstacles in clarifying the identity of traditional types of reputation, for they are mostly words of mouth passed among members of a society. However, due to dramatic technological advancement and widespread use of the Internet and social media, now we can clearly see and analyze written reputations, which used to be passed only from mouth to mouth. Against this background, this study examines whether a negativity bias-a notion that an event of a more negative nature has a greater effect on one's psychological state than a positive event-applies to spread of reputation online, and examines related factors and effects. To this end, reputation-related online comments left by social media users during the election period of Korea's 6th provincial election on 4 June 2014 were analyzed. For the analysis, a Bass diffusion model was used, which is based on the innovation diffusion theory. The analysis results confirmed that, at online forum, negative reputations spread more quickly and more widely than positive ones, had a greater impact, and mass media such as online news outlets had a significant influence on spread of reputation online.

• International Journal of Advanced Culture Technology
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• v.7 no.1
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• pp.77-83
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• 2019

Recently, as social media users have grown, the resulting form of advertising has emerged, and one of the types is native advertising. This advertising method appears to be 52% higher than the banner, according to a study by the IPG Media Lab (2013). Therefore, there is a positive effect on native advertising, but it is necessary to maximize the effect. In this paper, the acceptor's attitude to the native advertisement and the shared intention are verified as to how the effect of the native advertisement can be understood and the maximized effect can be obtained. When the brand phrase was in the form of direct exposure, the subjects were positive about the advertisement and the brand attitude was favorable. Share intentions were also high. These results included suggestions to produce native advertisements in consideration of the attitudes and sharing of the recipients.

• Journal of Preventive Medicine and Public Health
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• v.54 no.1
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• pp.22-30
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• 2021

Objectives: The coronavirus disease 2019 (COVID-19) pandemic is a public health emergency posing unprecedented challenges for health authorities. Social media may serve as an effective platform to disseminate health-related information. This study aimed to assess the extent of social media use, its impact on preventive behavior, and negative health effects such as cyberchondria and information overload. Methods: A cross-sectional observational study was conducted between June 10, 2020 and August 9, 2020 among people visiting the outpatient department of the authors' institution, and participants were also recruited during field visits for an awareness drive. Questions were developed on preventive behavior, and the Short Cyberchondria Scale and instruments dealing with information overload and perceived vulnerability were used. Results: The study recruited 767 participants with a mean age of about 45 years. Most of the participants (>90%) engaged in preventive behaviors, which were influenced by the extent of information received through social media platforms (β=3.297; p<0.001) and awareness of infection when a family member tested positive (β=29.082; p<0.001) or a neighbor tested positive (β=27.964; p<0.001). The majority (63.0%) of individuals often searched for COVID-19 related news on social media platforms. The mean±standard deviation scores for cyberchondria and information overload were 9.09±4.05 and 8.69±2.56, respectively. Significant and moderately strong correlations were found between cyberchondria, information overload, and perceived vulnerability to COVID-19. Conclusions: This study provides evidence that the use of social media as an information- seeking platform altered preventive behavior. However, excessive and misleading information resulted in cyberchondria and information overload.

• Asia-Pacific Journal of Business
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• v.15 no.2
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• pp.1-22
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• 2024

Purpose - The Chinese fan community includes a significant number of young and middle-aged individuals, playing a crucial role in emotional mobilization and social engagement. In recent years, the impact of Celebrity Pairing or Character Pairing (CP) on Weibo has grown notably, partly due to features like Super Topics and Hot Searches. This phenomenon has enhanced fan engagement, resulting in heightened participation in discussions and interactions on the platform. Our study targets CP fans of movies and television dramas on Weibo and aims to identify the factors that drive their emotional sharing. Design/methodology/approach - The research methodology integrates Self-Determination Theory and Social Sharing of Emotion Theory within the EASI (Emotion, Attachment, and Social Integration) model. This approach aims to uncover how CP fans meet their emotional needs via social media and determine the factors influencing their sharing intentions and behaviours. Data were collected through online surveys, yielding 504 valid responses Findings - The analysis, performed with SPSS and Smart PLS software, reveals that self-determination, interpersonal relationships, and social media tolerance significantly affect fans' intentions to share content. Specifically, intrinsic motivation, driven by self-determination, is a critical factor in CP fans' propensity to share content, highlighting the importance of 'inward socialization.' Additionally, the study finds that external factors, like the social media environment, play a more minor role than internal motivators. Research implications or Originality - This research enhances quantitative research methodologies by identifying intrinsic and extrinsic motivations that satisfy the emotional needs of CP fans. It distinguishes between individual, interpersonal, and collective/social factors as motivational elements, providing insights into the emotional and psychological needs of the Chinese movie and TV drama fan community.