Review analysis of ride-sharing applications using machine learning approaches: Bangladesh perspective

Taminul Islam, Arindom Kundu, Rishalatun Jannat Lima, Most Hasna Hena, Omar Sharif, Azizur Rahman, Md Zobaer Hasan

Research output: Book chapter/Published conference paperChapter (peer-reviewed)peer-review

11 Citations (Scopus)

Abstract

Technology and ride-sharing services have become more accessible and convenient as a result of the growth of the Internet. Passengers increasingly focus on digital reviews to help them make purchasing decisions. Online reviews are incredibly inaccurate, as we have seen time and time again. False reviews were created to deceive customers for commercial purposes. A misleading review might have major repercussions for any organization. Organization is focused on providing good feedback to attract passengers and grow the market. It is possible that a bad review of an app would reduce interest in it. These false reviews endanger the reputation of a product. Because of this, it is critical to have a system in place for detecting fraudulent reviews. This research aims to improve the performance of machine learning models that classify fake reviews. This research aims to contribute to the authenticity of reviews using contemporary techniques and the data from ride-sharing apps. This contribution is vital and significant in a country where ride-sharing apps are becoming more convenient and useful. We created a fresh dataset using different apps-based reviews from the current Bangladesh ride-sharing users’ review section. In this work Decision tree, Random Forest, Gradient Boosting, AdaBoost, and Bi-LSTM machine learning approaches were implemented to get the best performance on our dataset. After creating and running the model, Bidirectional Long Short-Term Memory (Bi-LSTM) achieved 85% best accuracy and 85.0 F1 score with training data rather than other machine learning algorithms.
Original languageEnglish
Title of host publicationComputational statistical methodologies and modelling for Artificial Intelligence
EditorsPriyanka Harjule, Azizur Rahman, Basant Agarwal, Vinita Tiwari
Place of PublicationBoca Raton
PublisherCRC Press
Chapter5
Pages130-158
Number of pages24
Edition1
ISBN (Electronic)9781003253051
ISBN (Print)9781032170800
DOIs
Publication statusPublished - 01 Jan 2023

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