PDF(Pubmed)
Abstract：
BACKGROUND: The proliferation of misinformation on social media is a significant concern due to its frequent occurrence and subsequent adverse social consequences. Effective interventions for and corrections of misinformation have become a focal point of scholarly inquiry. However, exploration of the underlying causes that affect the public acceptance of misinformation correction is still important and not yet sufficient.
OBJECTIVE: This study aims to identify the critical attributions that influence public acceptance of misinformation correction by using attribution analysis of aspects of public sentiment, as well as investigate the differences and similarities in public sentiment attributions in different types of misinformation correction.
METHODS: A theoretical framework was developed for analysis based on attribution theory, and public sentiment attributions were divided into 6 aspects and 11 dimensions. The correction posts for the 31 screened misinformation events comprised 33,422 Weibo posts, and the corresponding Weibo comments amounted to 370,218. A pretraining model was used to assess public acceptance of misinformation correction from these comments, and the aspect-based sentiment analysis method was used to identify the attributions of public sentiment response. Ultimately, this study revealed the causality between public sentiment attributions and public acceptance of misinformation correction through logistic regression analysis.
RESULTS: The findings were as follows: First, public sentiments attributed to external attribution had a greater impact on public acceptance than those attributed to internal attribution. The public associated different aspects with correction depending on the type of misinformation. The accuracy of the correction and the entity responsible for carrying it out had a significant impact on public acceptance of misinformation correction. Second, negative sentiments toward the media significantly increased, and public trust in the media significantly decreased. The collapse of media credibility had a detrimental effect on the actual effectiveness of misinformation correction. Third, there was a significant difference in public attitudes toward the official government and local governments. Public negative sentiments toward local governments were more pronounced.
CONCLUSIONS: Our findings imply that public acceptance of misinformation correction requires flexible communication tailored to public sentiment attribution. The media need to rebuild their image and regain public trust. Moreover, the government plays a central role in public acceptance of misinformation correction. Some local governments need to repair trust with the public. Overall, this study offered insights into practical experience and a theoretical foundation for controlling various types of misinformation based on attribution analysis of public sentiment.
OBJECTIVE: This study aims to identify the critical attributions that influence public acceptance of misinformation correction by using attribution analysis of aspects of public sentiment, as well as investigate the differences and similarities in public sentiment attributions in different types of misinformation correction.
METHODS: A theoretical framework was developed for analysis based on attribution theory, and public sentiment attributions were divided into 6 aspects and 11 dimensions. The correction posts for the 31 screened misinformation events comprised 33,422 Weibo posts, and the corresponding Weibo comments amounted to 370,218. A pretraining model was used to assess public acceptance of misinformation correction from these comments, and the aspect-based sentiment analysis method was used to identify the attributions of public sentiment response. Ultimately, this study revealed the causality between public sentiment attributions and public acceptance of misinformation correction through logistic regression analysis.
RESULTS: The findings were as follows: First, public sentiments attributed to external attribution had a greater impact on public acceptance than those attributed to internal attribution. The public associated different aspects with correction depending on the type of misinformation. The accuracy of the correction and the entity responsible for carrying it out had a significant impact on public acceptance of misinformation correction. Second, negative sentiments toward the media significantly increased, and public trust in the media significantly decreased. The collapse of media credibility had a detrimental effect on the actual effectiveness of misinformation correction. Third, there was a significant difference in public attitudes toward the official government and local governments. Public negative sentiments toward local governments were more pronounced.
CONCLUSIONS: Our findings imply that public acceptance of misinformation correction requires flexible communication tailored to public sentiment attribution. The media need to rebuild their image and regain public trust. Moreover, the government plays a central role in public acceptance of misinformation correction. Some local governments need to repair trust with the public. Overall, this study offered insights into practical experience and a theoretical foundation for controlling various types of misinformation based on attribution analysis of public sentiment.
摘要：
背景：由于其频繁发生和随后的不良社会后果，社交媒体上错误信息的扩散是一个重大问题。有效干预和纠正错误信息已成为学术研究的重点。然而,探索影响公众接受错误信息纠正的根本原因仍然很重要，还不够充分。
目的：本研究旨在通过对公众情绪方面的归因分析，确定影响公众接受错误信息纠正的关键归因，以及调查不同类型的错误信息更正中公众情绪归因的差异和相似性。
方法：建立了基于归因理论的分析理论框架，公众情绪归因分为6个方面和11个维度。31个被筛选的错误信息事件的更正帖子包括33,422个微博帖子，相应的微博评论达370,218条。使用预训练模型来评估公众对这些评论中错误信息纠正的接受程度，并采用基于方面的情感分析方法识别公众情绪反应的归因。最终,本研究通过logistic回归分析揭示了公众情绪归因与公众接受错误信息纠正之间的因果关系。
结果：研究结果如下：首先，与归因于内部归属的公众情绪相比，归因于外部归属的公众情绪对公众接受的影响更大。公众根据错误信息的类型将不同方面与更正相关联。更正的准确性和负责执行更正的实体对公众接受错误信息更正产生了重大影响。第二,对媒体的负面情绪明显增加，公众对媒体的信任显著下降。媒体信誉的崩溃对纠正错误信息的实际效果产生了不利影响。第三，公众对官方政府和地方政府的态度存在显着差异。公众对地方政府的负面情绪更为明显。
结论：我们的发现表明，公众接受错误信息纠正需要针对公众情绪归因进行灵活的沟通。媒体需要重建自己的形象，重新获得公众的信任。此外，政府在公众接受错误信息纠正方面发挥着核心作用。一些地方政府需要修复与公众的信任。总的来说,这项研究为基于公众情绪的归因分析控制各种类型的错误信息提供了实践经验和理论基础。
目的：本研究旨在通过对公众情绪方面的归因分析，确定影响公众接受错误信息纠正的关键归因，以及调查不同类型的错误信息更正中公众情绪归因的差异和相似性。
方法：建立了基于归因理论的分析理论框架，公众情绪归因分为6个方面和11个维度。31个被筛选的错误信息事件的更正帖子包括33,422个微博帖子，相应的微博评论达370,218条。使用预训练模型来评估公众对这些评论中错误信息纠正的接受程度，并采用基于方面的情感分析方法识别公众情绪反应的归因。最终,本研究通过logistic回归分析揭示了公众情绪归因与公众接受错误信息纠正之间的因果关系。
结果：研究结果如下：首先，与归因于内部归属的公众情绪相比，归因于外部归属的公众情绪对公众接受的影响更大。公众根据错误信息的类型将不同方面与更正相关联。更正的准确性和负责执行更正的实体对公众接受错误信息更正产生了重大影响。第二,对媒体的负面情绪明显增加，公众对媒体的信任显著下降。媒体信誉的崩溃对纠正错误信息的实际效果产生了不利影响。第三，公众对官方政府和地方政府的态度存在显着差异。公众对地方政府的负面情绪更为明显。
结论：我们的发现表明，公众接受错误信息纠正需要针对公众情绪归因进行灵活的沟通。媒体需要重建自己的形象，重新获得公众的信任。此外，政府在公众接受错误信息纠正方面发挥着核心作用。一些地方政府需要修复与公众的信任。总的来说,这项研究为基于公众情绪的归因分析控制各种类型的错误信息提供了实践经验和理论基础。
