Description

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.

OCLC

1250025758

Document Type

Dataset

DCMI Type

Dataset

File Format

.zip, .txt, .xlsx

Publication Date

4-20-2021

Funder

NSF, Division of Social and Economic Sciences (SES)

Publisher

Utah State University

Award Number

NSF, Division of Social and Economic Sciences (SES) 1459903

Award Title

Collaborative Research: Multi-scale Modeling of Public Perceptions of Heat Wave Risk

Methodology

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.

Referenced by

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

Start Date

6-1-2016

End Date

8-31-2016

Language

eng

Code Lists

See the README.txt file.

Disciplines

Environmental Health and Protection | Environmental Sciences | Other Environmental Sciences

License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Identifier

https://doi.org/10.26078/3gay-z874

Checksum

eccb5212a2fedbe0488f735a0f424f36

Additional Files

README.txt (4 kB)
MD5: 157fe8b06a6e976e13db37604b4063ea

Data_on_the_Effects.xlsx (123 kB)
MD5: e75faa0cfd2e735405a14d39f3257307

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