PDF(Pubmed)
Abstract：
BACKGROUND: Social media has become an increasingly popular and critical tool for users to digest diverse information and express their perceptions and attitudes. While most studies endeavor to delineate the emotional responses of social media users, there is limited research exploring the factors associated with the emergence of emotions, particularly negative ones, during news consumption.
OBJECTIVE: We aim to first depict the web coverage by news organizations on social media and then explore the crucial elements of news coverage that trigger the public\'s negative emotions. Our findings can act as a reference for responsible parties and news organizations in times of crisis.
METHODS: We collected 23,705 Facebook posts with 1,019,317 comments from the public pages of representative news organizations in Hong Kong. We used text mining techniques, such as topic models and Bidirectional Encoder Representations from Transformers, to analyze news components and public reactions. Beyond descriptive analysis, we used regression models to shed light on how news coverage on social media is associated with the public\'s negative emotional responses.
RESULTS: Our results suggest that occurrences of issues regarding pandemic situations, antipandemic measures, and supportive actions are likely to reduce the public\'s negative emotions, while comments on the posts mentioning the central government and the Government of Hong Kong reveal more negativeness. Negative and neutral media tones can alleviate the rage and interact with the subjects and issues in the news to affect users\' negative emotions. Post length is found to have a curvilinear relationship with users\' negative emotions.
CONCLUSIONS: This study sheds light on the impacts of various components of news coverage (issues, subjects, media tone, and length) on social media on the public\'s negative emotions (anger, fear, and sadness). Our comprehensive analysis provides a reference framework for efficient crisis communication for similar pandemics at present or in the future. This research, although first extending the analysis between the components of news coverage and negative user emotions to the scenario of social media, echoes previous studies drawn from traditional media and its derivatives, such as web newspapers. Although the era of COVID-19 pandemic gradually brings down the curtain, the commonality of this research and previous studies also contributes to establishing a clearer territory in the field of health crises.
OBJECTIVE: We aim to first depict the web coverage by news organizations on social media and then explore the crucial elements of news coverage that trigger the public\'s negative emotions. Our findings can act as a reference for responsible parties and news organizations in times of crisis.
METHODS: We collected 23,705 Facebook posts with 1,019,317 comments from the public pages of representative news organizations in Hong Kong. We used text mining techniques, such as topic models and Bidirectional Encoder Representations from Transformers, to analyze news components and public reactions. Beyond descriptive analysis, we used regression models to shed light on how news coverage on social media is associated with the public\'s negative emotional responses.
RESULTS: Our results suggest that occurrences of issues regarding pandemic situations, antipandemic measures, and supportive actions are likely to reduce the public\'s negative emotions, while comments on the posts mentioning the central government and the Government of Hong Kong reveal more negativeness. Negative and neutral media tones can alleviate the rage and interact with the subjects and issues in the news to affect users\' negative emotions. Post length is found to have a curvilinear relationship with users\' negative emotions.
CONCLUSIONS: This study sheds light on the impacts of various components of news coverage (issues, subjects, media tone, and length) on social media on the public\'s negative emotions (anger, fear, and sadness). Our comprehensive analysis provides a reference framework for efficient crisis communication for similar pandemics at present or in the future. This research, although first extending the analysis between the components of news coverage and negative user emotions to the scenario of social media, echoes previous studies drawn from traditional media and its derivatives, such as web newspapers. Although the era of COVID-19 pandemic gradually brings down the curtain, the commonality of this research and previous studies also contributes to establishing a clearer territory in the field of health crises.
摘要：
背景：社交媒体已成为用户消化各种信息并表达其看法和态度的日益流行和关键的工具。虽然大多数研究都试图描述社交媒体用户的情绪反应，探索与情绪出现相关因素的研究有限，尤其是负面的，在新闻消费中。
目的：我们的目标是首先在社交媒体上描绘新闻机构的网络报道，然后探索引发公众负面情绪的新闻报道的关键因素。我们的发现可以在危机时期为负责任的各方和新闻机构提供参考。
方法：我们从香港代表性新闻机构的公共页面收集了23,705条Facebook帖子和1,019,317条评论。我们使用了文本挖掘技术，如主题模型和来自变压器的双向编码器表示，分析新闻成分和公众反应。除了描述性分析，我们使用回归模型来揭示社交媒体上的新闻报道如何与公众的负面情绪反应相关联。
结果：我们的结果表明，关于大流行情况的问题的发生，抗大流行措施，和支持行动可能会减少公众的负面情绪，而对提到中央政府和香港政府的帖子的评论则显示出更多的负面影响。负面和中性的媒体音调可以缓解愤怒，并与新闻中的主题和问题互动，以影响用户的负面情绪。帖子长度被发现与用户的负面情绪有曲线关系。
结论：这项研究揭示了新闻报道各个组成部分的影响（问题，主题,媒体音调,和长度)在社交媒体上对公众的负面情绪(愤怒，恐惧,和悲伤）。我们的综合分析为当前或将来类似流行病的有效危机沟通提供了参考框架。这项研究,尽管首先将新闻报道和负面用户情绪的组成部分之间的分析扩展到社交媒体的场景，呼应了以前来自传统媒体及其衍生物的研究，比如网络报纸。尽管COVID-19大流行的时代逐渐落下帷幕，这项研究与以往研究的共同性也有助于在健康危机领域建立更清晰的领域。
目的：我们的目标是首先在社交媒体上描绘新闻机构的网络报道，然后探索引发公众负面情绪的新闻报道的关键因素。我们的发现可以在危机时期为负责任的各方和新闻机构提供参考。
方法：我们从香港代表性新闻机构的公共页面收集了23,705条Facebook帖子和1,019,317条评论。我们使用了文本挖掘技术，如主题模型和来自变压器的双向编码器表示，分析新闻成分和公众反应。除了描述性分析，我们使用回归模型来揭示社交媒体上的新闻报道如何与公众的负面情绪反应相关联。
结果：我们的结果表明，关于大流行情况的问题的发生，抗大流行措施，和支持行动可能会减少公众的负面情绪，而对提到中央政府和香港政府的帖子的评论则显示出更多的负面影响。负面和中性的媒体音调可以缓解愤怒，并与新闻中的主题和问题互动，以影响用户的负面情绪。帖子长度被发现与用户的负面情绪有曲线关系。
结论：这项研究揭示了新闻报道各个组成部分的影响（问题，主题,媒体音调,和长度)在社交媒体上对公众的负面情绪(愤怒，恐惧,和悲伤）。我们的综合分析为当前或将来类似流行病的有效危机沟通提供了参考框架。这项研究,尽管首先将新闻报道和负面用户情绪的组成部分之间的分析扩展到社交媒体的场景，呼应了以前来自传统媒体及其衍生物的研究，比如网络报纸。尽管COVID-19大流行的时代逐渐落下帷幕，这项研究与以往研究的共同性也有助于在健康危机领域建立更清晰的领域。
