Dataset: tweets and events linked to the paper 'Open-domain extraction of future events from Twitter'

DOI

Input data and output of research conducted in the study described in the paper:F. Kunneman and A. Van den Bosch (2016), Open-domain extraction of future events from Twitter, Natural Language Engineering, doi: 10.1017/S1351324916000036The paper describes a system that extracts future referring time expressions and entities from Twitter messages, and subsequently detects events as a pair of a date and entity the are often mentioned in the same tweet. This dataset features the ids of a large set of Dutch tweets posted in August 2014, which was used as input to the system, as well as the time expression and / or entity that was extracted from each tweet, if any. Furthermore, the detected events are included, represented as a date, one or more describing terms, the tweetids that refer to it and the assessment of the event by human annotators.

Identifier
DOI https://doi.org/10.17026/dans-227-36wn
Metadata Access https://phys-techsciences.datastations.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.17026/dans-227-36wn
Provenance
Creator F.A. Kunneman; A.P.J. van den Bosch
Publisher DANS Data Station Phys-Tech Sciences
Contributor RU Radboud University
Publication Year 2017
Rights CC BY 4.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/licenses/by/4.0
OpenAccess true
Contact RU Radboud University
Representation
Resource Type Dataset
Format text/plain; charset=US-ASCII; application/octet-stream; application/zip; text/plain; application/pdf
Size 94; 151; 189; 1272; 379; 284; 474; 132; 740; 303; 1025; 550; 227; 170; 417; 265; 341; 835; 113; 873; 208; 1595; 246; 512; 436; 854; 322; 683; 626; 816; 398; 702; 144; 569; 455; 930; 2241; 721; 607; 588; 911; 1633; 431638; 1386; 759; 493; 360; 364695; 987; 778; 1709; 531; 645; 797; 1177; 1215; 2792; 1063; 1823; 949; 892; 55247; 1158; 664; 525949774; 815769173; 1652; 1405
Version 2.0
Discipline Other