Data

tweetexploR

Queensland University of Technology
QUT Digital Observatory
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25912/RDF_1676860790823&rft.title=tweetexploR&rft.identifier=10.25912/RDF_1676860790823&rft.publisher=Queensland University of Technology&rft.description=About tweetexploR is an R package for exploring and visualising a collection of Tweets that has been tidied into an SQLite database file by the tidy_tweet library. tweetexploR allows you to quickly answer questions such as: How many tweets are there per hour/day/month? How many times did each user post a tweet? How many unique users posted tweets per hour/day/month? What are the most frequently used hashtags? Which tweets were liked the most? Who is being mentioned the most? Who is being replied to the most? Which tweets were retweeted the most? Which accounts were retweeted the most? What are the engagement metrics for the tweets? tweetexploR uses ggplot2 to create nicely formatted charts, and even allows you to tweak them to suit your own preferences. tweetexploR also gives you the option to export the data underlying each visualisation.  for the development version of tweetexploR, and supporting are provided on GitHub (see Download for the link to GitHub). &rft.creator=QUT Digital Observatory &rft.date=2023&rft.edition=1.0&rft_rights=© Digital Observatory, Queensland University of Technology, 2022.&rft_rights=MIT Licence - https://opensource.org/license/mit/&rft_subject=Social media analysis&rft_subject=Social science&rft.type=dataset&rft.language=English Access the data
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MIT Licence - https://opensource.org/license/mit/

© Digital Observatory, Queensland University of Technology, 2022.

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Use the link in the Downloads section to access the source code.

MIT Licence conditions also apply to the use of this source code:

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Contact Information

Postal Address:
Digital Observatory

digitalobservatory@qut.edu.au

Full description

About

tweetexploR is an R package for exploring and visualising a collection of Tweets that has been tidied into an SQLite database file by the tidy_tweet library.

tweetexploR allows you to quickly answer questions such as:

  • How many tweets are there per hour/day/month?
  • How many times did each user post a tweet?
  • How many unique users posted tweets per hour/day/month?
  • What are the most frequently used hashtags?
  • Which tweets were liked the most?
  • Who is being mentioned the most?
  • Who is being replied to the most?
  • Which tweets were retweeted the most?
  • Which accounts were retweeted the most?
  • What are the engagement metrics for the tweets?

tweetexploR uses ggplot2 to create nicely formatted charts, and even allows you to tweak them to suit your own preferences. tweetexploR also gives you the option to export the data underlying each visualisation.

 for the development version of tweetexploR, and supporting are provided on GitHub (see Download for the link to GitHub).

Data time period: 26 08 2022 to 07 09 2022

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Subjects
Social media analysis | Social science |

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