In this paper we describe the iTACOS submission for the Stance and Gender Detection in Tweets on Catalan Independence shared task. Concerning the detection of stance, we ranked as the first position in both languages outperforming the baselines; while in gender detection we ranked as fourth and third for Catalan and Spanish. Our approach is based on three diverse groups of features: stylistic, structural and context-based. We introduced two novel features that exploit significant characteristics conveyed by the presence of Twitter marks and URLs. The results of our experiments are promising and will lead to future tailoring of these two features in a finer grained manner.

iTACOS at IberEval2017: Detecting Stance in Catalan and Spanish Tweets

Mirko Lai;CIGNARELLA, ALESSANDRA TERESA;Delia Irazú Hernández Farías
2017-01-01

Abstract

In this paper we describe the iTACOS submission for the Stance and Gender Detection in Tweets on Catalan Independence shared task. Concerning the detection of stance, we ranked as the first position in both languages outperforming the baselines; while in gender detection we ranked as fourth and third for Catalan and Spanish. Our approach is based on three diverse groups of features: stylistic, structural and context-based. We introduced two novel features that exploit significant characteristics conveyed by the presence of Twitter marks and URLs. The results of our experiments are promising and will lead to future tailoring of these two features in a finer grained manner.
IberEval 2017
Murcia, Spain
19 September
Evaluation of Human Language Technologies for Iberian Languages Workshop 2017
CEUR-WS.org
1881
185
192
http://ceur-ws.org/Vol-1881/StanceCat2017_paper_2.pdf
https://www.researchgate.net/publication/317638270_iTACOS_at_IberEval2017_Detecting_Stance_in_Catalan_and_Spanish_Tweets
Lai, Mirko; Cignarella, ALESSANDRA TERESA; HERNANDEZ FARIAS, DELIA IRAZU
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1652433
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