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oaioai:www.clarin.si:11356/1054

Twitter sentiment for 15 European languages

Authors
Publication date
23 February 2016
Publisher
Jožef Stefan Institute
Doi

    Abstract

    The dataset contains over 1.6 million tweets (tweet IDs), labeled with sentiment by human annotators. There are 15 Twitter corpora for the corresponding 15 European languages. The data can be used to train and evaluate Twitter sentiment classifiers, to compute annotator agreement, or to study the differences between language usage on Twitter. The data analysis is described in the following papers: I. Mozetič, M. Grčar, J. Smailović. Multilingual Twitter sentiment classification: The role of human annotators, PLoS ONE 11(5): e0155036, doi: 10.1371/journal.pone.e0155036, 2016. (http://dx.doi.org/10.1371/journal.pone.0155036) I. Mozetič, L. Torgo, V. Cerqueira, J. Smailović. How to evaluate sentiment classifiers for Twitter time-ordered data?, PLoS ONE 13(3): e0194317, doi: 10.1371/journal.pone.0194317, 2018. (https://dx.doi.org/10.1371/journal.pone.0194317

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    Common Language Resources and Technology Infrastructure - Slovenia

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    oaioai:www.clarin.si:11356/1054
    Last time updated on 07/05/2019

    This paper was published in Common Language Resources and Technology Infrastructure - Slovenia.

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