BPA: A Multilingual Sentiment Analysis Approach based on BiLSTM

Iago Chaves, Antônio Martins, Francisco Praciano, Felipe Brito, Jose Monteiro, Javam Machado

2022

Abstract

Sentiment analysis (SA) is the automatic process of understanding people’s feelings or beliefs expressed in texts such as emotions, opinions, attitudes, appraisals and others. The main task is to identify the polarity level (positive, neutral or negative) of a given text. This task has been the subject of several research competitions in many languages, for instance, English, Spanish and Arabic. However, developing a multilingual sentiment analysis method remains a challenge. In this paper, we propose a new approach, called BPA, based on BiLSTM neural networks, pooling operations and attention mechanism, which is able to automatically classify the polarity level of a text. We evaluated the BPA approach using five different data sets in three distinct languages: English, Spanish and Portuguese. Experimental results evidence the suitability of the proposed approach to multilingual and domain-independent polarity classification. BPA’s best results achieved an accuracy of 0.901, 0.865 and 0.923 for English, Spanish and Portuguese, respectively.

Paper Citation

in Harvard Style

Chaves I., Martins A., Praciano F., Brito F., Monteiro J. and Machado J. (2022). BPA: A Multilingual Sentiment Analysis Approach based on BiLSTM. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-569-2, pages 553-560. DOI: 10.5220/0011071400003179

in Bibtex Style

@conference{iceis22,
author={Iago Chaves and Antônio Martins and Francisco Praciano and Felipe Brito and Jose Monteiro and Javam Machado},
title={BPA: A Multilingual Sentiment Analysis Approach based on BiLSTM},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2022},
pages={553-560},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011071400003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - BPA: A Multilingual Sentiment Analysis Approach based on BiLSTM
SN - 978-989-758-569-2
AU - Chaves I.
AU - Martins A.
AU - Praciano F.
AU - Brito F.
AU - Monteiro J.
AU - Machado J.
PY - 2022
SP - 553
EP - 560
DO - 10.5220/0011071400003179