Text Mining and Sentiment Classification for Logistics Enterprises Evaluation Based on BERT

Lihang Cheng, Siyuan Guo, Yifan Liu, Yi Zhuang

2024

Abstract

Abstract： In the era of community internet and intelligent industry, evaluation text data, as a novel alternative data resource, is widely utilized by the industrial and commercial sector. In this paper, we innovatively stand in the perspective of logistics industrial informatics, consider evaluation text and sentiment features as the key information reflecting the satisfaction of logistics enterprises, and construct experiments using pre-trained models, and consider them as one of the normalized data for sentiment classification. In other words, deep learning techniques were utilized to analyze the user evaluations of each logistics enterprise on the microblogging platform, which were fed into the Bert model to discriminate the sentiment polarity, and were able to classify the predictions with a high degree of accuracy. It provides a path to further extract the distribution of emotional tendency and the evaluation theme words of logistics enterprises from the text data, which expands the perspective and dimension of users’ choice of logistics enterprises, and also helps the logistics enterprises to improve their services based on the evaluation, and helps the development of the logistics industry and the evaluation research system of logistics management from the side of alternative data mining and analysis.

Paper Citation

in Harvard Style

Cheng L., Guo S., Liu Y. and Zhuang Y. (2024). Text Mining and Sentiment Classification for Logistics Enterprises Evaluation Based on BERT. In Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS; ISBN 978-989-758-715-3, SciTePress, pages 113-118. DOI: 10.5220/0012928600004536

in Bibtex Style

@conference{dmeis24,
author={Lihang Cheng and Siyuan Guo and Yifan Liu and Yi Zhuang},
title={Text Mining and Sentiment Classification for Logistics Enterprises Evaluation Based on BERT},
booktitle={Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS},
year={2024},
pages={113-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012928600004536},
isbn={978-989-758-715-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Mining, E-Learning, and Information Systems - Volume 1: DMEIS
TI - Text Mining and Sentiment Classification for Logistics Enterprises Evaluation Based on BERT
SN - 978-989-758-715-3
AU - Cheng L.
AU - Guo S.
AU - Liu Y.
AU - Zhuang Y.
PY - 2024
SP - 113
EP - 118
DO - 10.5220/0012928600004536
PB - SciTePress