This dataset contains Twitter messages about heat hazards posted by U.S. National Weather Service accounts in 2016. The dataset also contains the retweet counts of the heat-related tweets and whether several types of persuasive message content were included in each tweet. The population and temperature for the forecast area of each sending National Weather Service account are also included.
Author ORCID Identifier
Yajie Li https://orcid.org/0000-0002-3286-7384
Amanda L. Hughes https://orcid.org/0000-0002-7506-3343
Peter D Howe https://orcid.org/0000-0002-1555-3746
.zip, .txt, .xlsx
NSF, Division of Social and Economic Sciences (SES)
Utah State University
NSF, Division of Social and Economic Sciences (SES) 1459903
Collaborative Research: Multi-scale Modeling of Public Perceptions of Heat Wave Risk
Using Twitter search application programming interface, heat-related tweets were collected if tweets were posted between June 1, 2016 and August 31, 2016 by one of sampled U.S. National Weather Service offices. Human coding was conducted to determine whether each tweet included persuasive message content. The population size was derived from the U.S. Census Bureau, and the temperature variables were derived from the PRISM Climate Group. See associated publication for details of these data.
Li, Y., Hughes, A. L., & Howe, P. D. (2021). Toward Win-win Message Strategies: The Effects of Persuasive Message Content on Retweet Counts During Natural Hazard Events. Weather, Climate, and Society. https://doi.org/10.1175/WCAS-D-20-0039.1
See the README.txt file.
Environmental Health and Protection | Environmental Sciences | Other Environmental Sciences
This work is licensed under a Creative Commons Attribution 4.0 License.
Li, Y., Hughes, A. L., & Howe, P. D. (2021). Data on the Effects of Persuasive Message Content on Retweet Counts during Natural Hazard Events. Utah State University. https://doi.org/10.26078/3GAY-Z874
Additional FilesREADME.txt (4 kB)
Data_on_the_Effects.xlsx (123 kB)