Teamsters and Teamsters Locals Tweets
Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)
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Title |
Teamsters and Teamsters Locals Tweets
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Identifier |
https://doi.org/10.7910/DVN/UOJ6KG
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Creator |
Smallen, Vakil
Kerchner, Daniel |
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Publisher |
Harvard Dataverse
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Description |
This dataset contains the tweet ids of 63,707 tweets posted by the Twitter accounts of the International Brotherhood of Teamsters as well as affiliated locals. The purpose of the collection was to document the experience of Teamsters members as front line workers, as well as the union's role in supporting its members, during the COVID-19 pandemic. This data was collected as part of the IBT COVID-19 Response Collection at George Washington University Libraries Special Collections. Tweets were collected between May 8, 2020 and Feb. 23, 2022, from the GET statuses/user_timeline method of the Twitter v1 REST API using Social Feed Manager. Collecting from the Twitter timelines harvests some tweets that were posted prior to the collection date, so this collection includes tweets as far back as 2015 in some cases. The teamsters_locals_ids.txt file contains the IDs of the tweets collected. The list of screen names included in the collection can be found in the teamsters_locals_filter_README.txt file. The teamsters_locals_filter_README.txt file also contains additional documentation on how the tweets were collected, including the dates and times that screen names were added to collecting, and when collections occurred. The GET statuses/lookup method supports retrieving the complete tweet for a tweet ID (known as hydrating). Tools such as Twarc or Hydrator can be used to hydrate tweets. Per Twitter’s Developer Policy, tweet ids may be publicly shared for academic purposes; tweets may not. Questions about this dataset can be sent to sfm@gwu.edu. George Washington University researchers should contact us for access to the tweets. |
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Subject |
Social Sciences
Labor Unions International Brotherhood of Teamsters Workplace Safety COVID-19 Coronavirus Pandemic COVID19 |
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Language |
English
French Spanish, Castilian |
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Contributor |
Kerchner, Daniel
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Type |
social media data
Twitter Data |
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