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...

Full description

Bibliographic Details
Main Authors: Joshua J. Vertalka, Eva Kassens-Noor, Mark Wilson
Format: Article
Language:English
Published: Elsevier 2019-06-01
Series:Data in Brief
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340919302203
id doaj-6598f8314ec54e4baffb608e2c4eba5f
record_format Article
spelling 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 AT joshuajvertalka dataonsentimentsandemotionsofolympicthemedtweets
AT evakassensnoor dataonsentimentsandemotionsofolympicthemedtweets
AT markwilson dataonsentimentsandemotionsofolympicthemedtweets
_version_ 1724912493354024960