Analysing the Sentiments in Online Reviews with Special Focus on Automobile Market

Ayman Yafoz, Farial Syed, Malek Mouhoub, Lisa Fan

2022

Abstract

Analysing the sentiments in online reviews assists in understanding customers’ satisfaction with a provided service or product, which gives the industry an opportunity to enhance the quality of their commodity, increase sales volume, develop marketing strategies, improve response to customers, promote customer satisfaction, and enhance the industry image. However, the studies focusing on applying machine learning algorithms and word embedding models, as well as deep learning techniques to classify the sentiments in reviews extracted from automobile forums, are arguably limited, and to fill this gap, this research addressed this area. Moreover, the research concentrated on categorizing positive, negative, and mixed sentiment categories in online forum reviews. The procedures for gathering and preparing the dataset are illustrated in this research. To perform the classification task, a set of models which include supervised machine learning, deep learning, and BERT word embedding is adopted in this research. The results show that the combination of the BERT word embedding model with the LSTM model produced the highest F1 score. Finally, the paper lays out recommendations to enhance the proposed system in future studies.

Paper Citation

in Harvard Style

Yafoz A., Syed F., Mouhoub M. and Fan L. (2022). Analysing the Sentiments in Online Reviews with Special Focus on Automobile Market. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-547-0, pages 261-267. DOI: 10.5220/0010812100003116

in Bibtex Style

@conference{icaart22,
author={Ayman Yafoz and Farial Syed and Malek Mouhoub and Lisa Fan},
title={Analysing the Sentiments in Online Reviews with Special Focus on Automobile Market},
booktitle={Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2022},
pages={261-267},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010812100003116},
isbn={978-989-758-547-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Analysing the Sentiments in Online Reviews with Special Focus on Automobile Market
SN - 978-989-758-547-0
AU - Yafoz A.
AU - Syed F.
AU - Mouhoub M.
AU - Fan L.
PY - 2022
SP - 261
EP - 267
DO - 10.5220/0010812100003116