Purpose

Misinformation is notoriously difficult to combat. Although social media firms have focused on combating the publication of misinformation, misinformation accusations, an important by-product of the spread of misinformation, have been neglected. The authors offer insights into factors contributing to the spread of misinformation accusations on social media platforms.

Design/methodology/approach

The authors use a corpus of 234,556 tweets about the 2020 US presidential election (Study 1) and 99,032 tweets about the 2022 US midterm elections (Study 2) to show how the sharing of misinformation accusations is explained by locomotion orientation.

Findings

The study findings indicate that the sharing of misinformation accusations is explained by writers' lower locomotion orientation, which is amplified among liberal tweet writers.

Research limitations/implications

Practitioners and policymakers can use the study findings to track and reduce the spread of misinformation accusations by developing algorithms to analyze the language of posts. A limitation of this research is that it focuses on political misinformation accusations. Future research in different contexts, such as vaccines, would be pertinent.

Practical implications

The authors show how social media firms can identify messages containing misinformation accusations with the potential to become viral by considering the tweet writer's locomotion language and geographical data.

Social implications

Early identification of messages containing misinformation accusations can help to improve the quality of the political conversation and electoral decision-making.

Originality/value

Strategies used by social media platforms to identify misinformation lack scale and perform poorly, making it important for social media platforms to manage misinformation accusations in an effort to retain trust. The authors identify linguistic and geographical factors that drive misinformation accusation retweets.

中文翻译：

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你在说谎！错误信息指控如何在 Twitter 上传播

目的

众所周知，错误信息很难打击。尽管社交媒体公司一直致力于打击错误信息的发布，但错误信息指控这一错误信息传播的重要副产品却被忽视了。作者对导致社交媒体平台上错误信息指控传播的因素提供了见解。

设计/方法论/途径

作者使用包含 234,556 条关于 2020 年美国总统大选的推文（研究 1）和 99,032 条关于 2022 年美国中期选举的推文（研究 2）的语料库来展示如何通过运动方向来解释错误信息指控的分享。

发现

研究结果表明，错误信息指控的传播是由于作者的较低运动倾向造成的，这种倾向在自由派推文作者中被放大。

研究局限性/影响

从业者和政策制定者可以利用研究结果，通过开发算法来分析帖子的语言，来跟踪和减少错误信息指控的传播。这项研究的局限性在于它侧重于政治错误信息指控。未来在不同背景下的研究，例如疫苗，将是相关的。

实际影响

作者展示了社交媒体公司如何通过考虑推文作者的运动语言和地理数据来识别包含错误信息指控并有可能病毒式传播的消息。

社会影响

及早识别包含错误信息指控的信息有助于提高政治对话和选举决策的质量。

原创性/价值

社交媒体平台用于识别错误信息的策略缺乏规模且效果不佳，因此社交媒体平台管理错误信息指控以保持信任非常重要。作者确定了导致错误信息指控转发的语言和地理因素。