Prediction of sentiment polarity in restaurant reviews using an ordinal regression approach based on evolutionary XGBoost.

ABSTRACT: As the business world shifts to the web and tremendous amounts of data become available on multilingual mobile applications, new business and research challenges and opportunities have been explored. This research aims to intensify the usage of data analytics, machine learning, and sentiment analysis of textual data to classify customers' reviews, feedback, and ratings of businesses in Jordan's food and restaurant industry. The main methods used in this research were sentiment polarity (to address the challenges posed by businesses to automatically apply text analysis) and bio-metric techniques (to systematically identify users' emotional states, so reviews can be thoroughly understood). The research was extended to deal with reviews in Arabic, dialectic Arabic, and English, with the main

SUBMITTER: Al-Qudah DA 

PROVIDER: S-EPMC11784868 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature