Scholarlink

This study explores people’s views on Bangladesh railways through opinion polls that examine public opinion through sources such as Social media. We aim to provide a simple understanding of the railway’s outlook by focusing on positive, negative and neutral comments. These findings are important for policy makers and railway authorities to improve services, solve problems and improve the overall user experience. This research helps create a more efficient, customer-focused and enjoyable railway system for the people of Bangladesh. After using Machine Learning Algorithm like SVM, Naïve Bayes, Decision Tree, Random Forest, Logistic Regression, Ensemble Learning we got 84% accuracy for Ensemble Learning and to understand of people’s sentiment on Bangladesh Railway System.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Harnessing Machine Learning to Analyze Passenger Sentiments in the Bangladesh Railway System

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Manoara Begum,
  • Md Jahirul Haque Rifat,
  • Tanjim Mahmud,
  • Mohammad Tarek Aziz,
  • Nurullaeva Nodira,
  • Atayev Shokir,
  • Abubokor Hanip,
  • Mohammad Shahadat Hossain

摘要

This study explores people’s views on Bangladesh railways through opinion polls that examine public opinion through sources such as Social media. We aim to provide a simple understanding of the railway’s outlook by focusing on positive, negative and neutral comments. These findings are important for policy makers and railway authorities to improve services, solve problems and improve the overall user experience. This research helps create a more efficient, customer-focused and enjoyable railway system for the people of Bangladesh. After using Machine Learning Algorithm like SVM, Naïve Bayes, Decision Tree, Random Forest, Logistic Regression, Ensemble Learning we got 84% accuracy for Ensemble Learning and to understand of people’s sentiment on Bangladesh Railway System.