Feature Selection with Hybrid Bio-inspired Approach for Classifying Multi-idiom Social Media Sentiment Analysis

Luís Silva, Carlos Valêncio, Geraldo Zafalon, Angelo Columbini

2022

Abstract

Social media sentiment analysis consists on extracting information from users’ comments. It can assist the decision-making process of companies, aid public health and security and even identify intentions and opinions about candidates in elections. However, such data come from an environment with big data characteristics, which can make traditional and manual analysis impracticable because of the high dimensionality. The implications on the analysis are high computational cost and low quality of results. Up to date research focuses on how to analyse feelings of users with machine learning and inspired by nature methods. To analyse such data effectively, a feature selection through cuckoo search and genetic algorithm is proposed. Machine learning with lexical analysis has become an attractive alternative to overcome this challenge. This paper aims to present a hybrid bio-inspired approach to realize feature selection and improve sentiment classification quality. The scientific contribution is the improvement of a classification model considering pre-processing of the data with different languages and contexts. The results prove that the developed method enriches the predictive model. There is an improvement of around 13% in accuracy with a 45% average usage of attributes related to traditional analysis.

Paper Citation

in Harvard Style

Silva L., Valêncio C., Zafalon G. and Columbini A. (2022). Feature Selection with Hybrid Bio-inspired Approach for Classifying Multi-idiom Social Media Sentiment Analysis. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-569-2, pages 297-307. DOI: 10.5220/0010972800003179

in Bibtex Style

@conference{iceis22,
author={Luís Silva and Carlos Valêncio and Geraldo Zafalon and Angelo Columbini},
title={Feature Selection with Hybrid Bio-inspired Approach for Classifying Multi-idiom Social Media Sentiment Analysis},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2022},
pages={297-307},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010972800003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Feature Selection with Hybrid Bio-inspired Approach for Classifying Multi-idiom Social Media Sentiment Analysis
SN - 978-989-758-569-2
AU - Silva L.
AU - Valêncio C.
AU - Zafalon G.
AU - Columbini A.
PY - 2022
SP - 297
EP - 307
DO - 10.5220/0010972800003179