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人们认为社交媒体平台会(但不应该)放大分裂内容。

People Think That Social Media Platforms Do (but Should Not) Amplify Divisive Content.

机构信息

Department of Psychology & Center for Neural Science, New York University.

Kellogg School of Management, Northwestern University.

出版信息

Perspect Psychol Sci. 2024 Sep;19(5):781-795. doi: 10.1177/17456916231190392. Epub 2023 Sep 26.

Abstract

Recent studies have documented the type of content that is most likely to spread widely, or go "viral," on social media, yet little is known about people's perceptions of what goes viral or what should go viral. This is critical to understand because there is widespread debate about how to improve or regulate social media algorithms. We recruited a sample of participants that is nationally representative of the U.S. population (according to age, gender, and race/ethnicity) and surveyed them about their perceptions of social media virality ( = 511). In line with prior research, people believe that divisive content, moral outrage, negative content, high-arousal content, and misinformation are all likely to go viral online. However, they reported that this type of content should not go viral on social media. Instead, people reported that many forms of positive content-such as accurate content, nuanced content, and educational content-are not likely to go viral even though they think this content should go viral. These perceptions were shared among most participants and were only weakly related to political orientation, social media usage, and demographic variables. In sum, there is broad consensus around the type of content people think social media platforms should and should not amplify, which can help inform solutions for improving social media.

摘要

最近的研究记录了最有可能在社交媒体上广泛传播或“病毒式传播”的内容类型,但人们对什么是病毒式传播以及什么应该传播知之甚少。这一点至关重要,因为人们对如何改进或规范社交媒体算法存在广泛的争论。我们招募了一组具有全国代表性的参与者样本(根据年龄、性别和种族/族裔),对他们对社交媒体病毒式传播的看法进行了调查(=511)。与先前的研究一致,人们认为分裂性内容、道德愤慨、负面内容、高唤醒内容和错误信息都很可能在网上病毒式传播。然而,他们报告说,这类内容不应该在社交媒体上传播。相反,人们报告说,许多形式的正面内容,如准确的内容、细致的内容和教育性的内容,即使他们认为这些内容应该传播,也不太可能在网上传播。这些看法在大多数参与者中都得到了认同,而且与政治取向、社交媒体使用和人口统计学变量的关系较弱。总之,人们对社交媒体平台应该和不应该放大的内容类型有广泛的共识,这可以为改进社交媒体提供信息。

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