A new corpus-based convolutional neural network for big data text analytics

被引:3
作者
Nahili, Wedjdane [1 ]
Rezeg, Kahled [1 ]
Kazar, Okba [1 ]
机构
[1] Biskra Univ, Comp Sci, LINFI Lab, Biskra, Algeria
来源
JOURNAL OF INTELLIGENCE STUDIES IN BUSINESS | 2019年 / 9卷 / 02期
关键词
Convolutional neural networks; deep learning; natural language processing; NLP; user reviews; sentiment analysis; text classification;
D O I
10.37380/jisib.v9i2.469
中图分类号
F [经济];
学科分类号
02 ;
摘要
Companies market their services and products on social media platforms with today's easy access to the internet. As result, they receive feedback and reviews from their users directly on their social media sites. Reading every text is time-consuming and resource-demanding. With access to technology-based solutions, analyzing the sentiment of all these texts gives companies an overview of how positive or negative users are on specific subjects will minimize losses. In this paper, we propose a deep learning approach to perform sentiment analysis on reviews using a convolutional neural network model, because that they have proven remarkable results for text classification. We validate our convolutional neural network model using large-scale data sets: IMDB movie reviews and Reuters data sets with a final accuracy score of similar to 86% for both data sets.
引用
收藏
页码:59 / 71
页数:13
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