200K+ Crowdsourced Political Arguments for a New Chilean Constitution

Constanza Fierro; Claudio Fuentes; Jorge Pérez; Mauricio Quezada

doi:10.18653/v1/W17-5101

200K+ Crowdsourced Political Arguments for a New Chilean Constitution

Constanza Fierro, Claudio Fuentes, Jorge Pérez, Mauricio Quezada

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Abstract

In this paper we present the dataset of 200,000+ political arguments produced in the local phase of the 2016 Chilean constitutional process. We describe the human processing of this data by the government officials, and the manual tagging of arguments performed by members of our research group. Afterwards we focus on classification tasks that mimic the human processes, comparing linear methods with neural network architectures. The experiments show that some of the manual tasks are suitable for automatization. In particular, the best methods achieve a 90% top-5 accuracy in a multi-class classification of arguments, and 65% macro-averaged F1-score for tagging arguments according to a three-part argumentation model.

Anthology ID:: W17-5101
Volume:: Proceedings of the 4th Workshop on Argument Mining
Month:: September
Year:: 2017
Address:: Copenhagen, Denmark
Editors:: Ivan Habernal, Iryna Gurevych, Kevin Ashley, Claire Cardie, Nancy Green, Diane Litman, Georgios Petasis, Chris Reed, Noam Slonim, Vern Walker
Venue:: ArgMining
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 1–10
Language:
URL:: https://aclanthology.org/W17-5101/
DOI:: 10.18653/v1/W17-5101
Bibkey:
Cite (ACL):: Constanza Fierro, Claudio Fuentes, Jorge Pérez, and Mauricio Quezada. 2017. 200K+ Crowdsourced Political Arguments for a New Chilean Constitution. In Proceedings of the 4th Workshop on Argument Mining, pages 1–10, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):: 200K+ Crowdsourced Political Arguments for a New Chilean Constitution (Fierro et al., ArgMining 2017)
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PDF:: https://aclanthology.org/W17-5101.pdf

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@inproceedings{fierro-etal-2017-200k,
    title = "200{K}+ Crowdsourced Political Arguments for a New {C}hilean Constitution",
    author = "Fierro, Constanza  and
      Fuentes, Claudio  and
      P{\'e}rez, Jorge  and
      Quezada, Mauricio",
    editor = "Habernal, Ivan  and
      Gurevych, Iryna  and
      Ashley, Kevin  and
      Cardie, Claire  and
      Green, Nancy  and
      Litman, Diane  and
      Petasis, Georgios  and
      Reed, Chris  and
      Slonim, Noam  and
      Walker, Vern",
    booktitle = "Proceedings of the 4th Workshop on Argument Mining",
    month = sep,
    year = "2017",
    address = "Copenhagen, Denmark",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W17-5101/",
    doi = "10.18653/v1/W17-5101",
    pages = "1--10",
    abstract = "In this paper we present the dataset of 200,000+ political arguments produced in the local phase of the 2016 Chilean constitutional process. We describe the human processing of this data by the government officials, and the manual tagging of arguments performed by members of our research group. Afterwards we focus on classification tasks that mimic the human processes, comparing linear methods with neural network architectures. The experiments show that some of the manual tasks are suitable for automatization. In particular, the best methods achieve a 90{\%} top-5 accuracy in a multi-class classification of arguments, and 65{\%} macro-averaged F1-score for tagging arguments according to a three-part argumentation model."
}

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%0 Conference Proceedings
%T 200K+ Crowdsourced Political Arguments for a New Chilean Constitution
%A Fierro, Constanza
%A Fuentes, Claudio
%A Pérez, Jorge
%A Quezada, Mauricio
%Y Habernal, Ivan
%Y Gurevych, Iryna
%Y Ashley, Kevin
%Y Cardie, Claire
%Y Green, Nancy
%Y Litman, Diane
%Y Petasis, Georgios
%Y Reed, Chris
%Y Slonim, Noam
%Y Walker, Vern
%S Proceedings of the 4th Workshop on Argument Mining
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F fierro-etal-2017-200k
%X In this paper we present the dataset of 200,000+ political arguments produced in the local phase of the 2016 Chilean constitutional process. We describe the human processing of this data by the government officials, and the manual tagging of arguments performed by members of our research group. Afterwards we focus on classification tasks that mimic the human processes, comparing linear methods with neural network architectures. The experiments show that some of the manual tasks are suitable for automatization. In particular, the best methods achieve a 90% top-5 accuracy in a multi-class classification of arguments, and 65% macro-averaged F1-score for tagging arguments according to a three-part argumentation model.
%R 10.18653/v1/W17-5101
%U https://aclanthology.org/W17-5101/
%U https://doi.org/10.18653/v1/W17-5101
%P 1-10

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Markdown (Informal)

[200K+ Crowdsourced Political Arguments for a New Chilean Constitution](https://aclanthology.org/W17-5101/) (Fierro et al., ArgMining 2017)

200K+ Crowdsourced Political Arguments for a New Chilean Constitution (Fierro et al., ArgMining 2017)

ACL

Constanza Fierro, Claudio Fuentes, Jorge Pérez, and Mauricio Quezada. 2017. 200K+ Crowdsourced Political Arguments for a New Chilean Constitution. In Proceedings of the 4th Workshop on Argument Mining, pages 1–10, Copenhagen, Denmark. Association for Computational Linguistics.