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Research Article

EEO. 2021; 20(2): 827-836

Sentiment Analysis of Online Food Reviews using Big Data Analytics

Hafiz Muhammad Ahmed, Mazhar Javed Awan, Nabeel Sabir Khan, Awais Yasin, Hafiz Muhammad Faisal Shehzad.

Nowadays sentiment analysis has become very important, mostly used for huge datasets and helpful for researchers for applying methods and techniques. Amazonís food data is growing exponentially and traditional systems are unable to process it, so we used Big Data to overcome this problem. In this paper, we explore different methods and techniques of sentiment analysis using apache spark data processing system for big datasets of Amazon Fine Food reviews. Three mechanisms are applied that have more than 80% accuracy named as Linear SVC, Logistic Regression, and NaÔve Bayes by using MLlib which is Apache Sparkís library for ML. When applied these methods we realize that Linear SVC performs efficiently than NB and logistic regression.

Key words: Sentiment Analysis; Apache Spark; reviews, Machine Learning, Big Data, Analytics

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The articles in Bibliomed are open access articles licensed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, provided the work is properly cited.
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