Big Data Analytics Assisted Arithmetic Optimization with Deep Learning Model for Sentiment Classification
Big Data Analytics Assisted Arithmetic Optimization with Deep Learning Model for Sentiment Classification |
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| © 2023 by IJETT Journal | ||
| Volume-71 Issue-12 |
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| Year of Publication : 2023 | ||
| Author : K. Manivannan, T. Suresh, M. Parthiban |
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| DOI : 10.14445/22315381/IJETT-V71I12P206 | ||
How to Cite?
K. Manivannan, T. Suresh, M. Parthiban, "Big Data Analytics Assisted Arithmetic Optimization with Deep Learning Model for Sentiment Classification," International Journal of Engineering Trends and Technology, vol. 71, no. 12, pp. 50-60, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I12P206
Abstract
Sentiment Analysis (SA) may extract data from various text sources like blogs, reviews, and news; later, it categorizes them based on the polarity. Furthermore, big data is generated via social media and mobile networks. The implementation of SA on big data was found to be valuable for the business to take helpful commercial insights from textual-related content. Implementing SA on big data is utilized as a method to classify opinions into different sentiments. This article introduces a new Big Data Analytics Assisted Arithmetic Optimization with Deep Learning Model for Sentiment Classification (BDA-AODLSC) approach. The presented BDA-AODLSC approach exploits BDA tools for sentiment classification. Initially, the BDA-AODLSC approach performs data preprocessing to transform it into a compatible format, and the TF-IDF method is utilized for the word embedding process. An Attention-based Long Short-Term Memory (ALSTM) method is utilized for classifying sentiments, and its hyperparameters can be selected by an Arithmetic Optimization Algorithm (AOA). For managing big data, the Hadoop MapReduce tool is employed. A far-reaching analysis is accomplished to demonstrate the superior accomplishment of the BDA-AODLSC method. The extensive output demonstrates the significant accomplishment of the BDA-AODLSC method over other existing techniques.
Keywords
Sentiment analysis, Deep learning, Big data analytics, Arithmetic optimization algorithm, Hadoop MapReduce.
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