Detecting Dutch political tweets: A classifier based on voting system using supervised learning

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Abstract

The task of classifying political tweets has been shown to be very difficult, with controversial results in many works and with non-replicable methods. Most of the works with this goal use rule-based methods to identify political tweets. We propose here two methods, being one rule-based approach, which has an accuracy of 62%, and a supervised learning approach, which went up to 97% of accuracy in the task of distinguishing political and non-political tweets in a corpus of 2.881 Dutch tweets. Here we show that for a data base of Dutch tweets, we can outperform the rule-based method by combining many different supervised learning methods.

Original languageEnglish
Title of host publicationICAART 2018 - Proceedings of the 10th International Conference on Agents and Artificial Intelligence
Place of PublicationSetúbal
PublisherSciTePress
Pages462-469
Number of pages8
Volume2
ISBN (Electronic)9789897582752
DOIs
Publication statusPublished - Jan 2018
Event10th International Conference on Agents and Artificial Intelligence, ICAART 2018 - Funchal, Madeira, Portugal
Duration: 16 Jan 201818 Jan 2018

Conference

Conference10th International Conference on Agents and Artificial Intelligence, ICAART 2018
CountryPortugal
CityFunchal, Madeira
Period16/01/1818/01/18

Keywords

  • Dutch politics
  • Machine Learning
  • Natural Language Processing
  • Politics
  • Text Mining
  • Twitter

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