Paper 22 (Resources track)

TweetsKB: A Public and Large-Scale RDF Corpus of Annotated Tweets

Author(s): Pavlos Fafalios, Vasileios Iosifidis, Eirini Ntoutsi, Stefan Dietze

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.

Keywords: Twitter; RDF; Entity Linking; Sentiment Analysis; Social Media Archives

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