The influence of emotions on online information sharing behavior

Q2 Computer Science

Journal of Systems and Information Technology Pub Date : 2023-10-16 DOI:10.1108/jsit-03-2022-0060

Amal Dabbous, Karine Aoun Barakat

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引用次数: 0

Abstract

Purpose The spread of fake news represents a serious threat to consumers, companies and society. Previous studies have linked emotional arousal to an increased propensity to spread information and a decrease in people’s ability to recognize fake news. However, the effect of an individual’s emotional state on fake news sharing remains unclear, particularly during periods of severe disruptions such as pandemics. This study aims to fill the gap in the literature by elucidating how heightened emotions affect fake news sharing behavior. Design/methodology/approach To validate the conceptual model, this study uses a quantitative approach. Data were collected from 212 online questionnaires and then analyzed using the structural equation modeling technique. Findings Results of this study show that positive emotions have indirect effects on fake news sharing behavior by allowing users to view the quality of information circulating on social media in a more positive light, and increasing their socialization behavior leading them to share fake news. Negative emotions indirectly impact fake news sharing by affecting users’ information overload and reinforcing prior beliefs, which in turn increases fake news sharing. Research limitations/implications This study identifies several novel associations between emotions and fake news sharing behavior and offers a theoretical lens that can be used in future studies. It also provides several practical implications on the prevention mechanism that can counteract the dissemination of fake news. Originality/value This study investigates the impact of individuals’ emotional states on fake news sharing behavior, and establishes four user-centric antecedents to this sharing behavior. By focusing on individuals’ emotional state, cognitive reaction and behavioral response, it is among the first, to the best of the authors’ knowledge, to offer a multidimensional understanding of individuals’ interaction with news that circulates on social media.

查看原文本刊更多论文

情绪对网络信息分享行为的影响

假新闻的传播对消费者、企业和社会构成了严重威胁。之前的研究已经将情绪唤醒与传播信息的倾向增加和人们识别假新闻的能力下降联系起来。然而，个人情绪状态对假新闻分享的影响尚不清楚，尤其是在疫情等严重干扰时期。本研究旨在通过阐明情绪高涨如何影响假新闻分享行为来填补文献空白。设计/方法/方法为了验证概念模型，本研究采用了定量方法。通过212份在线问卷收集数据，采用结构方程建模技术对数据进行分析。本研究结果表明，积极情绪会间接影响假新闻分享行为，让用户更积极地看待社交媒体上传播的信息质量，并增加其社交行为，从而导致他们分享假新闻。负面情绪通过影响用户信息过载和强化先验信念间接影响假新闻分享，进而增加假新闻分享。本研究确定了情绪与假新闻分享行为之间的几种新联系，并为未来的研究提供了一个理论视角。它还为预防机制提供了一些实际意义，可以抵消假新闻的传播。本研究探讨了个体情绪状态对假新闻分享行为的影响，并建立了四个以用户为中心的假新闻分享行为前因。通过关注个人的情绪状态、认知反应和行为反应，据作者所知，这是第一次从多维角度理解个人与社交媒体上传播的新闻的互动。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Systems and Information Technology Computer Science-Computer Science (all)

CiteScore

4.40

自引率

0.00%

发文量

期刊介绍： The Journal provides an avenue for scholarly work that researches systems thinking applications, information systems, electronic business, data analytics, information sciences, information management, business intelligence, and complex adaptive systems in the application domains of the business environment, health, the built environment, cultural settings, and the natural environment. Papers examine the wider implications of the systems or technology being researched. This means papers consider aspects such as social and organisational relevance, business value, cognitive implications, social implications, impact on individuals or community perspectives, and the development of solutions, rather than focusing solely on the technology. The Journal of Systems and Information Technology is open to a wide range of research methodologies and paper styles including case studies, surveys, experiments, review papers, design science, design thinking and both theoretical and methodological papers. The focus of the journal will be to publish work that fits into the following broad areas of research: Behavioural Information Systems and Human-Computer Interaction, Data Analytics, Data, Information and Security, E-Business, Intelligent Systems and Applications, Logistics and Supply Chain Management/Optimisation, Social Media Analysis, Technology Enhanced Learning.