Data Sheet 1_Affect-inducing cues in risk messages: impact on collective negative emotions

A study analyzing how affect-inducing cues in risk messages influence collective negative emotions during public health emergencies. The data is derived from content and sentiment analysis of discussions about the COVID-19 variant 'Xbb' on the Chinese Q&A platform Zhihu. The dataset was authored by Tongtong Li and last updated on 2026-05-28.

Use Cases

• Modeling the relationship between fear appeal intensity and negative emotion prevalence based on the described inverted U-shaped finding.
• Analyzing the impact of risk stories on audience sentiment reduction as mentioned in the results.
• Testing sentiment analysis methods based on multiple lexicons and semantic rule sets for Chinese text.
• Investigating structural frameworks for collective emotional responses during health crises as discussed.

Strengths

• Dataset is licensed under CC-BY-4.0, permitting broad reuse with attribution.
• Analysis is focused on a specific public health event (COVID-19 variant Xbb) and time period (December 2022 to January 2023).
• The study introduces a specific sentiment analysis method for Chinese text based on multiple lexicons and semantic rules.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Data may reflect geographic and platform bias inherent to its source, Zhihu.

Provenance

Source

Discussions from the Chinese Q&A platform Zhihu.

Collection Method

Content analysis and fine-grained emotion analysis applied to online discussions.

Time Range

December 2022 to January 2023

Freshness

Last updated 2026-05-28 11:38:54; freshness should be verified.

Geography

Likely China-focused, based on the use of the Zhihu platform.