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Food delivery has become an integral part of daily life for many of the population. Undoubtedly, one of the main factors influencing people’s decision to purchase a product is the reviews and ratings given by other users to a particular restaurant. In this article, sentiment analysis is conducted on some reviews using NLP, employing ELM methods - Bagging and Voting - and machine learning algorithms such as MLP, KNN, and SVM, to achieve excellent predictions and determine the best ELM method for this situation. Our experiments revealed that Bagging with MLP yields good results, but Voting stands out the most, achieving the highest accuracy across all the tests in this article: 82.74%.

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Sentiment Analysis in Delivery Services Using Ensemble Learning Methods

  • 会议论文

  • 发表日期：

    2026年

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  • Paulo Henrique Ponte de Lucena,
  • Lidio Mauro Lima de Campos

摘要

Food delivery has become an integral part of daily life for many of the population. Undoubtedly, one of the main factors influencing people’s decision to purchase a product is the reviews and ratings given by other users to a particular restaurant. In this article, sentiment analysis is conducted on some reviews using NLP, employing ELM methods - Bagging and Voting - and machine learning algorithms such as MLP, KNN, and SVM, to achieve excellent predictions and determine the best ELM method for this situation. Our experiments revealed that Bagging with MLP yields good results, but Voting stands out the most, achieving the highest accuracy across all the tests in this article: 82.74%.