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Data on sentiments and emotions of olympic-themed tweets

Two code files and one dataset related to Olympic Twitter activity are the foundation for this article. Through Twitter's Spritzer streaming API (Application Programming Interface), we collected over 430 million tweets from May 12th, 2016 to September 12th, 2016 windowing the Rio de Janeiro Oly...

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Detalles Bibliográficos
Autores principales: Vertalka, Joshua J., Kassens-Noor, Eva, Wilson, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468189/
https://www.ncbi.nlm.nih.gov/pubmed/31016215
http://dx.doi.org/10.1016/j.dib.2019.103869
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author Vertalka, Joshua J.
Kassens-Noor, Eva
Wilson, Mark
author_facet Vertalka, Joshua J.
Kassens-Noor, Eva
Wilson, Mark
author_sort Vertalka, Joshua J.
collection PubMed
description Two code files and one dataset related to Olympic Twitter activity are the foundation for this article. Through Twitter's Spritzer streaming API (Application Programming Interface), we collected over 430 million tweets from May 12th, 2016 to September 12th, 2016 windowing the Rio de Janeiro Olympics and Paralympics. We cleaned and filtered these tweets to contain Olympic-related content. We then analyzed the raw data of 21,218,652 tweets including location data, language, and tweet content to distill the sentiment and emotions of Twitter users pertaining to the Olympic Games Kassens-Noor E. et al., 2019. We generalized the original data set to comply with the Twitter's Terms of Service and Developer agreement, 2018. We present the modified dataset and accompanying code files in this article to suggest using both for further analysis on sentiment and emotions related to the Rio de Janeiro Olympics and for comparative research on imagery and perceptions of other Olympic Games.
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spelling pubmed-64681892019-04-23 Data on sentiments and emotions of olympic-themed tweets Vertalka, Joshua J. Kassens-Noor, Eva Wilson, Mark Data Brief Social Science Two code files and one dataset related to Olympic Twitter activity are the foundation for this article. Through Twitter's Spritzer streaming API (Application Programming Interface), we collected over 430 million tweets from May 12th, 2016 to September 12th, 2016 windowing the Rio de Janeiro Olympics and Paralympics. We cleaned and filtered these tweets to contain Olympic-related content. We then analyzed the raw data of 21,218,652 tweets including location data, language, and tweet content to distill the sentiment and emotions of Twitter users pertaining to the Olympic Games Kassens-Noor E. et al., 2019. We generalized the original data set to comply with the Twitter's Terms of Service and Developer agreement, 2018. We present the modified dataset and accompanying code files in this article to suggest using both for further analysis on sentiment and emotions related to the Rio de Janeiro Olympics and for comparative research on imagery and perceptions of other Olympic Games. Elsevier 2019-03-20 /pmc/articles/PMC6468189/ /pubmed/31016215 http://dx.doi.org/10.1016/j.dib.2019.103869 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Social Science
Vertalka, Joshua J.
Kassens-Noor, Eva
Wilson, Mark
Data on sentiments and emotions of olympic-themed tweets
title Data on sentiments and emotions of olympic-themed tweets
title_full Data on sentiments and emotions of olympic-themed tweets
title_fullStr Data on sentiments and emotions of olympic-themed tweets
title_full_unstemmed Data on sentiments and emotions of olympic-themed tweets
title_short Data on sentiments and emotions of olympic-themed tweets
title_sort data on sentiments and emotions of olympic-themed tweets
topic Social Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6468189/
https://www.ncbi.nlm.nih.gov/pubmed/31016215
http://dx.doi.org/10.1016/j.dib.2019.103869
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