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“点赞”的重要性:信息框架、来源和社交认可对 Facebook 上健康信息可信度认知的相互作用。

The Importance of 'Likes': The Interplay of Message Framing, Source, and Social Endorsement on Credibility Perceptions of Health Information on Facebook.

机构信息

a GTZN 224, Edward R. Murrow College of Communication , Washington State University , Pullman , WA , USA.

出版信息

J Health Commun. 2018;23(4):399-411. doi: 10.1080/10810730.2018.1455770. Epub 2018 Mar 30.

DOI:10.1080/10810730.2018.1455770
PMID:29601271
Abstract

Online sources not only permeate the information-seeking environment of the younger generation, but also have profound influence in shaping their beliefs and behaviors. In this landscape, examining the factors responsible for credibility perceptions of online information is fundamental, particularly for health-related information. Using a 2 (frames: gain vs. loss) × 2 (source: expert vs. non-expert) × 2 (social endorsement: high vs. low) randomized between-subjects experimental design, this study examines the effect of health message framing and the moderating effects of social endorsement and source type on credibility perceptions of Facebook posts. Testing across two issues--physical activity and alcohol consumption--findings indicate that the gain-framed message was perceived as most credible. Additionally, significant three-way interactions suggest that social endorsement and source type affect the relationship between message framing and credibility perceptions. Specifically, the findings demonstrate that a gain-framed message from an expert source with high number of 'likes' is considered the most credible message. These findings have significant implications for information gathering from social media sources, such as the influence of 'likes' on health information.

摘要

在线资源不仅充斥着年轻一代的信息搜索环境,而且对他们的信仰和行为也有着深远的影响。在这种背景下,研究影响在线信息可信度感知的因素至关重要,特别是对于与健康相关的信息。本研究采用 2(框架:收益与损失)×2(来源:专家与非专家)×2(社会认可:高与低)的随机被试间实验设计,考察了健康信息的框架以及社会认可和来源类型对 Facebook 帖子可信度感知的调节作用。通过对两个问题——体育活动和饮酒消费的测试,结果表明,收益框架的信息被认为最可信。此外,显著的三向交互作用表明,社会认可和来源类型影响着信息框架和可信度感知之间的关系。具体来说,研究结果表明,来自具有高点赞数的专家来源的收益框架信息被认为是最可信的信息。这些发现对从社交媒体来源获取信息具有重要意义,例如“点赞”对健康信息的影响。

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