TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets
Pavlos Fafalios, Vasileios Iosifidis, Eirini Ntoutsi, Stefan Dietze

TL;DR
TweetsKB is a large, publicly accessible RDF corpus of over 1.5 billion tweets from 2013 to 2017, enriched with metadata, entities, hashtags, mentions, and sentiment data for research use.
Contribution
This paper introduces TweetsKB, a comprehensive, annotated Twitter dataset in RDF format, enabling advanced data exploration and integration for social media research.
Findings
Enables entity-centric information exploration.
Facilitates data integration and knowledge discovery.
Provides a large-scale, annotated Twitter corpus.
Abstract
Publicly available social media archives facilitate research in a variety of fields, such as data science, sociology or the digital humanities, where Twitter has emerged as one of the most prominent sources. However, obtaining, archiving and annotating large amounts of tweets is costly. In this paper, we describe TweetsKB, a publicly available corpus of currently more than 1.5 billion tweets, spanning almost 5 years (Jan'13-Nov'17). Metadata information about the tweets as well as extracted entities, hashtags, user mentions and sentiment information are exposed using established RDF/S vocabularies. Next to a description of the extraction and annotation process, we present use cases to illustrate scenarios for entity-centric information exploration, data integration and knowledge discovery facilitated by TweetsKB.
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