Application of Classification Model Based on Sentiment Tendency Data Mining in NLP Text Sentiment Analysis

Ke Yu

2022

Abstract

In order to study the application scenarios and effectiveness of various classification models in Natural Language Processing (NLP) text sentiment analysis, this paper compares several common text sentiment analysis classification models, and proposes a Bidirectional Encoder Representation based on Bidirectional Encoder Representation. The lightweight BERT (A Lite Bidirectional Encoder Representation from Transformers, ALBERT) pre-trained language model and Convolutional Recurrent Neural Network (CRNN), it is a new type of text sentiment analysis model ALBERT-CRNN that is optimized and transformed from Transformers (BERT) model. Through the construction of the ALBERT-CRNN model and the comparative analysis with the traditional language classification model, it is shown that the accuracy of the ALBERT-CRNN model on the three data sets reaches 94.1%, 93% and 95.5%, which is better than the traditional model. Therefore, the sentiment analysis model of barrage text constructed in this article can provide sufficient technical support for the current classification technology and text sentiment analysis.

Paper Citation

in Harvard Style

Yu K. (2022). Application of Classification Model Based on Sentiment Tendency Data Mining in NLP Text Sentiment Analysis. In Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI; ISBN 978-989-758-620-0, SciTePress, pages 682-686. DOI: 10.5220/0011754400003607

in Bibtex Style

@conference{icpdi22,
author={Ke Yu},
title={Application of Classification Model Based on Sentiment Tendency Data Mining in NLP Text Sentiment Analysis},
booktitle={Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI},
year={2022},
pages={682-686},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011754400003607},
isbn={978-989-758-620-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Public Management, Digital Economy and Internet Technology - Volume 1: ICPDI
TI - Application of Classification Model Based on Sentiment Tendency Data Mining in NLP Text Sentiment Analysis
SN - 978-989-758-620-0
AU - Yu K.
PY - 2022
SP - 682
EP - 686
DO - 10.5220/0011754400003607
PB - SciTePress