When AI Joins the Social Media Conversation: Exploring the Impact of Simulated AI-Assisted Comments on Health Risk Perceptions and Behaviors.

IF 2.7 3区 医学 Q1 COMMUNICATION
Xizhu Xiao, Chen Luo, Qinyan Song, Wenyuan Yang
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引用次数: 0

Abstract

Misinformation on social media has long been a pressing concern, and its spread is often exacerbated by social endorsement metrics such as likes and shares. While prior research has explored artificial intelligence (AI)-based strategies to combat misinformation, little attention has been given to how AI-powered functions (e.g. automated comments) shape user perceptions and behaviors in the context of social media misinformation. This study employs a 2 (misinformation social endorsement: high vs. low) × 3 (AI-suggested comments: approve misinformation vs. disapprove misinformation vs. no AI comments) between-subject experimental design, focusing on a health issue heavily affected by misinformation - HPV vaccination. The findings reveal that misinformation posts perceived as highly endorsed, either through social endorsement or AI-generated supportive comments, are viewed as most credible. Additionally, AI comments endorsing misinformation evoke greater fear under conditions of high social endorsement compared to the absence of AI comments. Conversely, AI comments challenging misinformation reduce the credibility of misinformation and mitigate fear surrounding HPV vaccination, but only under conditions of low social endorsement, relative to no AI comments. Credibility and fear emerge as critical mediators, influencing subsequent perceived risk of HPV vaccination and vaccination intentions. Theoretical and practical implications of these findings are discussed, shedding light on the nuanced interplay between AI interventions and social endorsement in addressing misinformation.

当人工智能加入社交媒体对话:探索模拟人工智能辅助评论对健康风险认知和行为的影响。
长期以来,社交媒体上的错误信息一直是一个紧迫的问题,它的传播往往会因点赞和分享等社会认可指标而加剧。虽然之前的研究已经探索了基于人工智能(AI)的策略来打击错误信息,但很少有人关注人工智能驱动的功能(例如自动评论)如何在社交媒体错误信息的背景下塑造用户的感知和行为。本研究采用2(错误信息社会认可:高vs低)× 3(人工智能建议评论:批准错误信息vs.不批准错误信息vs.没有人工智能评论)受试者间实验设计,重点关注受错误信息严重影响的健康问题- HPV疫苗接种。研究结果显示,无论是通过社会认可还是人工智能生成的支持性评论,被认为得到高度认可的错误信息帖子被认为是最可信的。此外,与没有人工智能评论相比,在高社会认可的情况下,人工智能评论支持错误信息会引起更大的恐惧。相反,挑战错误信息的人工智能评论降低了错误信息的可信度,减轻了人们对HPV疫苗接种的恐惧,但这只是在相对于没有人工智能评论的低社会认可条件下。信誉和恐惧成为关键的中介因素,影响HPV疫苗接种的后续感知风险和疫苗接种意图。本文讨论了这些发现的理论和实践意义,揭示了人工智能干预与社会认可在解决错误信息方面的微妙相互作用。
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
CiteScore
8.20
自引率
10.30%
发文量
184
期刊介绍: As an outlet for scholarly intercourse between medical and social sciences, this noteworthy journal seeks to improve practical communication between caregivers and patients and between institutions and the public. Outstanding editorial board members and contributors from both medical and social science arenas collaborate to meet the challenges inherent in this goal. Although most inclusions are data-based, the journal also publishes pedagogical, methodological, theoretical, and applied articles using both quantitative or qualitative methods.
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