Open Access
IEEE Access, volume 9, pages 134899-134915
A New Method for Stance Detection Based on Feature Selection Techniques and Ensembles of Classifiers
Kotelnikov Evgeny
1, 2
Publication type: Journal Article
Publication date: 2021-09-29
General Materials Science
General Engineering
General Computer Science
Abstract
Stance detection is one of the promising areas of computational linguistics, the task of which is to automatically recognize the author’s viewpoint on the target object. In our study, to detect the stance, we propose the Ensemble-based Stance Detection method (ESD). First, we calculate the optimal number of features that are most relevant to the given domain based on the function approximating the dependence of F1-score on the number of features. Then we form a relevant feature set using the homogeneous ensemble of feature selection methods. At last, we build the optimal composition of classifiers using the cross-validation procedure. Furthermore, we study the impact of various feature types on the performance in the stance detection task. The proposed ESD method is evaluated on the SemEval-2016 text corpus of tweets and the UKP Sentential Argument Mining corpus, and it outperforms the state-of-the-art systems.
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Neural Computing and Applications
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Neural Computing and Applications
1 publication, 25%
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Information Processing and Management
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Information Processing and Management
1 publication, 25%
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Springer Nature
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Springer Nature
1 publication, 25%
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Elsevier
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Elsevier
1 publication, 25%
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Vychegzhanin S., Kotelnikov E. A New Method for Stance Detection Based on Feature Selection Techniques and Ensembles of Classifiers // IEEE Access. 2021. Vol. 9. pp. 134899-134915.
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Vychegzhanin S., Kotelnikov E. A New Method for Stance Detection Based on Feature Selection Techniques and Ensembles of Classifiers // IEEE Access. 2021. Vol. 9. pp. 134899-134915.
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TY - JOUR
DO - 10.1109/access.2021.3116657
UR - https://doi.org/10.1109%2Faccess.2021.3116657
TI - A New Method for Stance Detection Based on Feature Selection Techniques and Ensembles of Classifiers
T2 - IEEE Access
AU - Vychegzhanin, Sergey
AU - Kotelnikov, Evgeny
PY - 2021
DA - 2021/09/29 00:00:00
PB - IEEE
SP - 134899-134915
VL - 9
SN - 2169-3536
ER -
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@article{2021_Vychegzhanin,
author = {Sergey Vychegzhanin and Evgeny Kotelnikov},
title = {A New Method for Stance Detection Based on Feature Selection Techniques and Ensembles of Classifiers},
journal = {IEEE Access},
year = {2021},
volume = {9},
publisher = {IEEE},
month = {sep},
url = {https://doi.org/10.1109%2Faccess.2021.3116657},
pages = {134899--134915},
doi = {10.1109/access.2021.3116657}
}