Summary information
Study title
TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets (Part 11, Jan 2022 - Aug 2022)
Creator
Baran, Erdal ( GESIS - Leibniz-Institut für Sozialwissenschaften)
Bensmann, Felix ( GESIS - Leibniz-Institut für Sozialwissenschaften)
Dietze, Stefan ( GESIS - Leibniz-Institut für Sozialwissenschaften & Heinrich-Heine-University Düsseldorf, Germany & L3S Research Center, Hannover, Germany)
Study number / PID
10.7802/2473 (GESIS)
10.7802/2473 (DOI)
Data access
Information not available
Series
Not available
Abstract
TweetsKB is a public RDF corpus of anonymized data for a large collection of annotated tweets. The dataset currently contains data for nearly 3.0 billion tweets, spanning more than 9 years (February 2013 - August 2022). Metadata information about the tweets as well as extracted entities, sentiments, hashtags, user mentions and URLs are exposed in RDF using established RDF/S vocabularies. For the sake of privacy, we anonymize user IDs and we do not provide the text of the tweets. For a list of the previous dataset parts, example queries and more information see the TweetsKB's home page: https://data.gesis.org/tweetskb/.
Topics
Keywords
Methodology
Data collection period
01/01/2022 - 01/08/2022
Country
Time dimension
Not availableAnalysis unit
Not availableUniverse
a 1% sample of all tweets from Jan 2022 until Aug 2022
Sampling procedure
Not availableKind of data
Not availableData collection mode
Web Scraping
Access
Publisher
GESIS Data Archive for the Social Sciences
Publication year
2022
Terms of data access
Free access (without registration) - The research data can be downloaded directly by anyone without further limitations.
Data can only be used for non-commercial research
Related publications
Not available