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arXiv 2401.02191cs.CY
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针对企业的虚假新闻特征分析

Characterizing Fake News Targeting Corporations

Ke Zhou, Sanja Scepanovic, Daniele Quercia

AI总结:

本研究利用社交媒体定量方法和众包研究分析S&P 500企业的虚假信息,发现其影响股票增长和员工情绪,并呈阶段性爆发,强调需警惕监测该现象。

摘要:

虚假信息在在线领域泛滥,对政治和社会领域产生了明显影响,影响了民主话语,并对公共健康和安全构成风险。企业界也是虚假新闻传播的主要目标。尽管最近的研究试图描述企业虚假信息及其对公司的影响,但由于定性或叙事方法以及对特定行业的狭窄关注,其发现往往受到限制。为了解决这一差距,我们利用社交媒体定量方法和众包研究,对S&P 500公司内多个不同行业的企业虚假信息进行了调查。我们的研究显示,企业虚假信息涵盖产品、政治和社会问题等主题。我们发现受虚假新闻影响的公司也会获得权威新闻报道,但社交媒体关注度较低,导致社交媒体评论中的负面情绪加剧,股票增长放缓,以及员工评论中压力提及增加。此外,我们观察到公司并非一直被虚假新闻针对,而是在特定时期会出现大量虚假新闻。这些发现对监管机构、商业领袖和投资者具有重要意义,强调必须警惕监测企业虚假信息不断升级的现象。

英文摘要:

Misinformation proliferates in the online sphere, with evident impacts on the political and social realms, influencing democratic discourse and posing risks to public health and safety. The corporate world is also a prime target for fake news dissemination. While recent studies have attempted to characterize corporate misinformation and its effects on companies, their findings often suffer from limitations due to qualitative or narrative approaches and a narrow focus on specific industries. To address this gap, we conducted an analysis utilizing social media quantitative methods and crowd-sourcing studies to investigate corporate misinformation across a diverse array of industries within the S\&P 500 companies. Our study reveals that corporate misinformation encompasses topics such as products, politics, and societal issues. We discovered companies affected by fake news also get reputable news coverage but less social media attention, leading to heightened negativity in social media comments, diminished stock growth, and increased stress mentions among employee reviews. Additionally, we observe that a company is not targeted by fake news all the time, but there are particular times when a critical mass of fake news emerges. These findings hold significant implications for regulators, business leaders, and investors, emphasizing the necessity to vigilantly monitor the escalating phenomenon of corporate misinformation.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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