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

Wedjdane Nahilia, Kahled Rezega, Okba Kazara


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 resourcedemanding. 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 ~86% for both data sets.


Convolutional neural networks, deep learning, natural language processing, NLP, user reviews, sentiment analysis, text classification

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DOI: https://doi.org/10.37380/jisib.v9i2.469


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