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A Twitter Sentiment Gold Standard for the Brexit Referendum

descriptionPublicationkeyboard_double_arrow_right Article , Conference object 12 Sep 2016Embargo end date: 14 Dec 2016 Ireland Publisher:ACMJournal:Proceedings of the 12th International Conference on Semantic SystemsPublicly fundedFunded by:EC | SSIX
Authors: Manuela Hürlimann; Brian Davis 0001; Keith Cortis; André Freitas; Siegfried Handschuh; Sergio Fernández;

doi: 10.1145/2993318.2993350 , 10.13025/21418 , 10.5281/zenodo.569251

handle: 10379/6241

A Twitter Sentiment Gold Standard for the Brexit Referendum

Abstract

A Twitter Sentiment Gold Standard for the Brexit Referendum Manuela Hürlimann, Brian Davis Insight Centre for Data Analytics National University of Ireland Galway, Ireland {first.last}@insight-centre.org Keith Cortis, André Freitas, Siegfried Handschuh University of Passau Germany {first.last}@uni-passau.de Sergio Fernández Redlink GmbH Salzburg Austria sergio.fernandez@redlink.co ABSTRACT In this paper, we present a sentiment-annotated Twitter gold standard for the Brexit referendum. The data set consists of 2,000 Twitter messages (“tweets”) annotated with information about the sentiment expressed, the strength of the sentiment, and context dependence. This is a valuable resource for social media-based opinion mining in the context of political events.

Country
Ireland
Related Organizations
Keywords

Political Opinion Mining, Annotation, Data analytics, Referendum, Twitter, Gold standard, Sentiment Analysis, Data Science Institute, Brexit

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citations
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BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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