Summary information
Study title
TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets (Part 12, Sep 2022 - Jun 2023)
Creator
Schellhammer, Sebastian ( GESIS - Leibniz-Institut für Sozialwissenschaften)
Baran, Erdal ( GESIS - Leibniz-Institut für Sozialwissenschaften)
Bensmann, Felix ( GESIS - Leibniz-Institut für Sozialwissenschaften)
Dimitrov, Dr. Dimitar ( GESIS - Leibniz-Institut für Sozialwissenschaften)
Dietze, Stefan ( GESIS - Leibniz-Institut für Sozialwissenschaften & Heinrich-Heine-University Düsseldorf, Germany & L3S Research Center, Hannover, Germany)
Zhang, Yudong ( GESIS - Leibniz-Institut für Sozialwissenschaften)
Study number / PID
10.7802/2781 (GESIS)
10.7802/2781 (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 more than 3.1 billion tweets, spanning more than 10 years (February 2013 - June 2023). 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
01/09/2022 - 01/06/2023
Country
Time dimension
Not availableAnalysis unit
Not availableUniverse
a 1% sample of all tweets from Sep 2022 unti Jun 2023
Sampling procedure
Not availableKind of data
Not availableData collection mode
Not availableAccess
Publisher
GESIS Data Archive for the Social Sciences
Publication year
2024
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