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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Online Access: | http://www.sciencedirect.com/science/article/pii/S2352340919302203 |
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doaj-6598f8314ec54e4baffb608e2c4eba5f2020-11-25T02:11:48ZengElsevierData in Brief2352-34092019-06-0124Data on sentiments and emotions of olympic-themed tweetsJoshua J. Vertalka0Eva Kassens-Noor1Mark Wilson2Resilient Solutions 21 (RS21), USAMichigan State University, USA; Corresponding author.Michigan State University, USATwo 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. Keywords: Olympic, R rdata, Twitter, Emotion lexiconhttp://www.sciencedirect.com/science/article/pii/S2352340919302203 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Joshua J. Vertalka Eva Kassens-Noor Mark Wilson |
spellingShingle |
Joshua J. Vertalka Eva Kassens-Noor Mark Wilson Data on sentiments and emotions of olympic-themed tweets Data in Brief |
author_facet |
Joshua J. Vertalka Eva Kassens-Noor Mark Wilson |
author_sort |
Joshua J. Vertalka |
title |
Data on sentiments and emotions of olympic-themed tweets |
title_short |
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_sort |
data on sentiments and emotions of olympic-themed tweets |
publisher |
Elsevier |
series |
Data in Brief |
issn |
2352-3409 |
publishDate |
2019-06-01 |
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. Keywords: Olympic, R rdata, Twitter, Emotion lexicon |
url |
http://www.sciencedirect.com/science/article/pii/S2352340919302203 |
work_keys_str_mv |
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