US EPA Twitter posts from 2013-2014 and 2017-2018

This dataset refers to posts made by the US EPA on Twitter (https://twitter.com/epa) during the years 2013-2014 and 2017-2018. Twitter (now X) was selected as one of the major social media platforms that government agencies use to communicate with the public. This data was analyzed for several discourse categories (e.g., speech acts, sentiment, expressives, actors, etc.) in a content analysis described in publications associated with this dataset. As of March 29, 2019, the EPA Twitter account had produced over 15,000 tweets and had over 595,000 followers. For reference, as of March 14, 2024, the account had about 623,000 followers. This data refers to a sample of all posts (not retweets and replies) made during the first 16 months of Administrator Gina McCarthy and the first 16 months of Administrator Scott Pruitt.

Methods
This data was collected in 2019 via the Twitter API. It contains references to posts (e.g., date post was made, link to post, etc.). It also contains coding of discourse categories (e.g., speech acts, sentiment, expressives, actors, etc.) performed in a content analysis of the messages as described in publications associated with this dataset. However, no text is provided here due to copyright restrictions. 

For research purposes, this data refers to a sample of all posts (not retweets and replies) collected from the EPA account. The population of posts was focused on the first 16 months of the administrator Gina McCarthy—a total of 4,765 posts from July 18, 2013, to December 14, 2014 (504 days); and the first 16 months of administrator Scott Pruitt, a total of 951 posts from February 17, 2017, to July 6, 2018 (504 days). 

From this data, we selected a random sample of 25% of the posts of the McCarthy full population of posts and 50% of the Pruitt full population of posts for a multi-annotator content analysis. This dataset here is a sample of 950 posts under the McCarthy administration and 471 posts under the Pruitt administration that were coded based on instructions developed for content analysis as described in related publications of this dataset.