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

Eric Fernandes de Mello Araújo; Dave Ebbelaar

doi:10.5220/0006592004620469

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

Eric Fernandes de Mello Araújo
, Dave Ebbelaar

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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 language	English
Title of host publication	Proceedings of the 10th International Conference on Agents and Artificial Intelligence
Subtitle of host publication	Volume 2: ICAART
Editors	Ana Paula Rocha, Jaap van den Herik
Place of Publication	Setúbal
Publisher	SciTePress
Pages	462-469
Number of pages	8
Volume	2
ISBN (Electronic)	9789897582752
DOIs	https://doi.org/10.5220/0006592004620469
Publication status	Published - 2018
Event	10th International Conference on Agents and Artificial Intelligence, ICAART 2018 - Funchal, Madeira, Portugal Duration: 16 Jan 2018 → 18 Jan 2018

Conference

Conference	10th International Conference on Agents and Artificial Intelligence, ICAART 2018
Country/Territory	Portugal
City	Funchal, Madeira
Period	16/01/18 → 18/01/18

Keywords

Dutch politics
Machine Learning
Natural Language Processing
Politics
Text Mining
Twitter

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10.5220/0006592004620469

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@inproceedings{215ca4f014734d50b6b532c5b740f8f9,

title = "Detecting Dutch political tweets: A classifier based on voting system using supervised learning",

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.",

keywords = "Dutch politics, Machine Learning, Natural Language Processing, Politics, Text Mining, Twitter",

author = "\{de Mello Ara{\'u}jo\}, \{Eric Fernandes\} and Dave Ebbelaar",

year = "2018",

doi = "10.5220/0006592004620469",

language = "English",

volume = "2",

pages = "462--469",

editor = "Rocha, \{Ana Paula\} and \{van den Herik\}, Jaap",

booktitle = "Proceedings of the 10th International Conference on Agents and Artificial Intelligence",

publisher = "SciTePress",

note = "10th International Conference on Agents and Artificial Intelligence, ICAART 2018 ; Conference date: 16-01-2018 Through 18-01-2018",

}

de Mello Araújo, EF & Ebbelaar, D 2018, Detecting Dutch political tweets: A classifier based on voting system using supervised learning. in AP Rocha & J van den Herik (eds), Proceedings of the 10th International Conference on Agents and Artificial Intelligence: Volume 2: ICAART. vol. 2, SciTePress, Setúbal, pp. 462-469, 10th International Conference on Agents and Artificial Intelligence, ICAART 2018, Funchal, Madeira, Portugal, 16/01/18. https://doi.org/10.5220/0006592004620469

Detecting Dutch political tweets: A classifier based on voting system using supervised learning. / de Mello Araújo, Eric Fernandes; Ebbelaar, Dave.
Proceedings of the 10th International Conference on Agents and Artificial Intelligence: Volume 2: ICAART. ed. / Ana Paula Rocha; Jaap van den Herik. Vol. 2 Setúbal: SciTePress, 2018. p. 462-469.

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Detecting Dutch political tweets

T2 - 10th International Conference on Agents and Artificial Intelligence, ICAART 2018

AU - de Mello Araújo, Eric Fernandes

AU - Ebbelaar, Dave

PY - 2018

Y1 - 2018

N2 - 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.

AB - 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.

KW - Dutch politics

KW - Machine Learning

KW - Natural Language Processing

KW - Politics

KW - Text Mining

KW - Twitter

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VL - 2

SP - 462

EP - 469

BT - Proceedings of the 10th International Conference on Agents and Artificial Intelligence

A2 - Rocha, Ana Paula

A2 - van den Herik, Jaap

PB - SciTePress

CY - Setúbal

Y2 - 16 January 2018 through 18 January 2018

ER -

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

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