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  11. Sentiment Analysis Of Arabic Social Media Texts: A Machine Learning Approach To Deciphering Customer Perceptions

Sentiment analysis of Arabic social media texts: A machine learning approach to deciphering customer perceptions

Ohud Alsemaree1, Atm S Alam1, Sukhpal Singh Gill1

  • 1School of Electronic Engineering and Computer Science, Queen Mary University of London, London, E1 4NS, UK.

Heliyon
|May 7, 2024

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View abstract on PubMed

Summary
This summary is machine-generated.

This study introduces an advanced Arabic sentiment analysis method for coffee product reviews, achieving over 95% accuracy. The new approach enhances understanding of customer opinions on social media.

Area of Science:

  • Artificial Intelligence
  • Natural Language Processing
  • Machine Learning

Background:

  • Customer sentiment analysis is crucial for the competitive coffee industry.
  • Traditional market analysis methods struggle to capture nuanced consumer views.
  • Arabic sentiment analysis is challenging due to complex language morphology.

Purpose of the Study:

  • To develop a precise and effective Arabic sentiment analysis method for coffee products.
  • To understand customer opinions on coffee products from social media data.
  • To aid businesses in making informed decisions about product promotion and improvement.

Main Methods:

  • Collected 10,646 Twitter reviews for various coffee products.
  • Applied Term Frequency-Inverse Document Frequency (TF-IDF) and Minimum Redundancy Maximum Relevance (MRMR) for feature extraction.
Keywords:
Arabic textFeature extractionMachine learningSentiment analysis

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  • Utilized k-nearest neighbor, support vector machine, decision tree, and random forest algorithms with ensemble learning for sentiment classification.

    • Main Results:

    • Achieved over 95.95% accuracy using Hard voting ensemble.
    • Reached 94.51% accuracy with soft voting ensemble.
    • Demonstrated improved prediction accuracy for Arabic sentiment analysis.

    Conclusions:

    • The developed method significantly enhances the precision of Arabic sentiment analysis for product reviews.
    • This approach provides valuable insights into consumer perceptions of coffee products.
    • The findings support data-driven decision-making for coffee businesses.
    Social media