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公众对社交媒体现场实验的态度。

Public attitudes towards social media field experiments.

机构信息

Leverhulme Centre for Demographic Science, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Public Policy Programme, Alan Turing Institute, London, UK.

出版信息

Sci Rep. 2024 Oct 30;14(1):26110. doi: 10.1038/s41598-024-76948-z.

DOI:10.1038/s41598-024-76948-z
PMID:39478029
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11525638/
Abstract

The growing use of social media field experiments demands a rethink of current research ethics in computational social science and psychological research. Here, we provide an exploratory empirical account of key user concerns and outline a number of critical discussions that need to take place to protect participants and help researchers to make use of the novel opportunities of digital data collection and field studies. Our primary contention is that we need to elicit public perceptions to devise more up-to-date guidelines for review boards whilst also allowing and encouraging researchers to arrive at more ethical individual study design choices themselves. To ground our discussion in real-world examples of online experiments, we focus on recent social media studies in the field of misinformation, polarization, and hate speech research. We conclude by discussing how we can better strike a balance between meeting ethical guidelines and the concerns of social media users alongside maximizing scientific impact and credibility.

摘要

社交媒体现场实验的使用日益增多,这要求我们重新思考计算社会科学和心理研究中的当前研究伦理。在这里,我们提供了对关键用户关注点的探索性实证描述,并概述了需要进行的一些重要讨论,以保护参与者并帮助研究人员利用数字数据收集和现场研究的新机会。我们的主要论点是,我们需要征求公众意见,为审查委员会制定更新的指导方针,同时允许并鼓励研究人员自行做出更符合伦理的个别研究设计选择。为了将我们的讨论建立在错误信息、极化和仇恨言论研究等社交媒体领域的在线实验的真实示例的基础上,我们重点介绍了最近的社交媒体研究。最后,我们讨论了如何在满足道德准则和社交媒体用户的担忧的同时,最大程度地提高科学影响力和可信度,更好地取得平衡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d0/11525638/ff761fe64d53/41598_2024_76948_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d0/11525638/49d87f7fbaed/41598_2024_76948_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d0/11525638/1305fff7ca40/41598_2024_76948_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d0/11525638/ff761fe64d53/41598_2024_76948_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d0/11525638/49d87f7fbaed/41598_2024_76948_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d0/11525638/1305fff7ca40/41598_2024_76948_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d0/11525638/ff761fe64d53/41598_2024_76948_Fig3_HTML.jpg

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Toolbox of individual-level interventions against online misinformation.个体层面干预网络错误信息工具箱。
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Online searches to evaluate misinformation can increase its perceived veracity.
在线搜索评估错误信息可能会增加其被感知的真实性。
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How to think about whether misinformation interventions work.如何思考错误信息干预措施是否有效。
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How do social media feed algorithms affect attitudes and behavior in an election campaign?社交媒体的推荐算法如何影响选举活动中的态度和行为?
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Resolving content moderation dilemmas between free speech and harmful misinformation.解决言论自由和有害错误信息之间的内容审核困境。
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Empathy-based counterspeech can reduce racist hate speech in a social media field experiment.基于同理心的反驳言论可以减少社交媒体领域实验中的种族主义仇恨言论。
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