Effects of Content Features and Lingual Form of Government Information Release on the Regulation of Public Negative Emotions During COVID-19 Epidemic in Wuhan

preprint OA: gold CC-BY-4.0
📄 Open PDF View at publisher

Abstract

Background: Emergencies and their associated negative emotions have a great effect on public health. As a key part of the emergency management, government information release (GIR) not only meets the public's health information seeking, but also helps to eliminate the breeding and spreading of negative social emotions. Method: From the two aspects of content features and lingual forms, a regression model was built to explore the mechanism of GIR on the regulation of netizens' negative emotions by adopting the theoretical methods of content analysis, emotion calculation, and case analysis. Results: During the emergency outbreak, if the government can timely release information on the incident and respond to the public using rational language, netizens' negative emotions can be alleviated. During the emergency peak, the government should release the event progress, resolution and disposal information to improve the recognition of netizens and eliminate negative emotions. Conclusions: According to different stages of emergencies, the government should timely and reasonably utilize the attitude tendency, content type and lingual form of GIR to effectively regulate the negative emotions of netizens.

My notes (saved in your browser only)

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.

Source provenance

europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-21T05:10:58.409756+00:00
License: CC-BY-4.0