U.S. Geotagged Twitter Posts with Daily State and County Aggregations

Geotagged Twitter posts from within the United States, organized by day, state, and county. The dataset includes tweet IDs and aggregated hashtag counts, along with shapefiles for U.S. administrative boundaries and Python scripts for data processing. It was created by Jürgen Pfeffer of Carnegie Mellon University and is available via paperswithcode under an Open Access (gold) license.

Use Cases

• Assessing geographic representativeness of social media data based on state and county-level tweet distributions.
• Analyzing regional trends in hashtag usage based on daily aggregated counts per state and county.
• Mapping social media activity to U.S. administrative boundaries using the provided shapefiles.
• Reproducing or extending the geotag sorting methodology using the included Python scripts.

Strengths

• Data is organized at multiple geographic granularities: daily files per state and per county.
• Includes aggregated hashtag counts, which can facilitate trend analysis without processing raw tweets.
• Provides ancillary resources like U.S. county and state shapefiles and Python scripts for data collection and sorting.

Limitations

• Row count and total volume of tweets are unknown, which may limit suitability assessment for large-scale studies.
• Column-level documentation is absent; field semantics must be inferred after download.
• Last update date is unknown; freshness unverified.

Provenance

Source

Carnegie Mellon University

Collection Method

Collection and sorting of geotagged Twitter posts, as indicated by the included Python scripts.

Geography

United States