A transformer based approach to detect the sentiment of drivers in ride sharing platforms

A transformer based approach to detect the sentiment of drivers in ride sharing platforms

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, 2024.

Opis bibliograficzny
1. autor:	Chakraborty, Sovon
Kolejni autorzy:	Sadeque, Farig Yousuf
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2024
Hasła przedmiotowe:	Machine learning XAI NLP Sentiment analysis Ride-sharing Sentiment analysis > Data processing. Natural language processing (Computer science).
Dostęp online:	http://hdl.handle.net/10361/24037

Podobne zapisy

Sentiment analysis using R: an approach to correlate bitcoin price fluctuations with change in user sentiments
od: Rahman, Shaomi, i wsp.
Wydane: (2018)

Women’s perceptions towards ride-sharing services: The case of Dhaka city
od: Nowshin, Nahela
Wydane: (2021)

Market acceptance of electronic car in ride sharing industry of Bangladesh
od: Ferdous, Afrin
Wydane: (2019)

Sentiment analysis on mobile operators’ customer review
od: Hossain, Mohammed Mohibul, i wsp.
Wydane: (2020)

A multimodal approach of sentiment analysis to predict customer emotions towards a product
od: Islam, Shadman, i wsp.
Wydane: (2020)

Microblog sentiment analysis for rating TV shows
od: Abdullah, Ashik
Wydane: (2017)

Human sentiment analysis using natural language processing
od: Shamya, Md. Shamiul Haque Khan, i wsp.
Wydane: (2024)

Sentimental analysis of customer product Reviews to understand customer needs using machine learning
od: Symum, Md Abdullah Al, i wsp.
Wydane: (2023)

Reducing traffic congestion through ride sharing in Bangladesh: a case study of Dhaka City
od: Mollah, Md Lokman Hossain
Wydane: (2021)

Sentiment analysis for Bengali newspaper headlines
od: Hossain, Mohammad Samman, i wsp.
Wydane: (2017)

Pathao ride share making Dhaka City people’s life easier
od: Rahman, Bantee
Wydane: (2022)

Analyzing users’ sentiment towards video games based on reviews from microblog
od: Roy, Abhijeet, i wsp.
Wydane: (2018)

Feature based mobile phone rating using sentiment analysis and machine learning approaches
od: Kafi, Abdullahil, i wsp.
Wydane: (2018)

An effective machine learning approach for sentiment analysis of restaurant reviews
od: Karim, Rabita
Wydane: (2018)

The Current state of ride-sharing apps in Bangladesh: are they successful in achieving customer satisfaction?
od: Al Muhit, Abdullah
Wydane: (2024)

Stock Market Price movement prediction using RNN and Point-weight Sentiment
od: Uddin, S. M. Rageeb Noor, i wsp.
Wydane: (2022)

Optimizing restaurant recommendations through sentiment analysis
od: Juha, Tasnia, i wsp.
Wydane: (2024)

Amazon product reviews sentiment analysis using supervised learning algorithms
od: Hawladar, Mohibullah, i wsp.
Wydane: (2021)

Conversational AI for companionship
od: Khan, Zakaria, i wsp.
Wydane: (2022)

Product rating generation based on public opinion using sentiment analysis
od: Rabbi, Reshan Ahmed, i wsp.
Wydane: (2018)

The use of digital application based platform for transport service by Pathao Limited.
od: Siddique, Abu Bakar
Wydane: (2020)

A framework for sentiment analysis: a data-driven approach
od: Islam, Md. Jahedul, i wsp.
Wydane: (2021)

Embedded system based bangla intelligent social virtual robot with sentiment analysis
od: Hossain, Md. Ishan Arefin, i wsp.
Wydane: (2018)

Sentiment classification on Bengali food and restaurant reviews
od: Hossain, Abid, i wsp.
Wydane: (2024)

Analyzing data of social media to evaluate customer behavior of companies using sentiment analysis
od: Shourin, Bushra, i wsp.
Wydane: (2018)

Share market forecasting with LSTM neural network and sentimental trend prediction
od: Rony, Ismail Hossain, i wsp.
Wydane: (2020)

Sentiment analysis in Bengali Text using NLP
od: Sarkar, Ankon, i wsp.
Wydane: (2023)

Unveiling underlying patterns, drivers and anomalies in cryptocurrency price dynamics through feature fusion of financial indicators and sentiment fluctuations
od: Rabbi, Md. Nafis
Wydane: (2024)

Into the heart of Bangla speech: advancing speech sentiment recognition with semi-supervised multimodal machine learning model leveraging an iterative SHAP-based feature selection
od: Shruti, Abanti Chakraborty
Wydane: (2024)

Performing sentiment analysis in Bangla microblog posts
od: Chowdhury, Shaika, i wsp.
Wydane: (2017)

Sentimental analysis on political speeches
od: Atiq, Asif, i wsp.
Wydane: (2022)

Aspect-based sentiment analysis using SemEval and Amazon datasets
od: Hasib, Tamanna, i wsp.
Wydane: (2018)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
od: Maliha, Miftahul Zannat, i wsp.
Wydane: (2023)

Sentiment analysis of customer reviews on food ordering portals of Bangladesh using natural language processing
od: Deb, Priom, i wsp.
Wydane: (2024)

Predicting stock market movement using sentiment analysis of twitter feed
od: Chakraborty, Pranjal, i wsp.
Wydane: (2017)

A machine learning approach to predict movie box-office success
od: Quader, Nahid, i wsp.
Wydane: (2018)

An advanced hospital rating system using machine learning and natural language processing
od: Tamjid, Ali Asgar, i wsp.
Wydane: (2023)

Detecting sarcasm in Bengali comments using NLP
od: Chowdhury, Md. Jamiur Rahman
Wydane: (2024)

Social media sentiment study on COVID-19 outbreak
od: Karmaker, Anik, i wsp.
Wydane: (2021)

Text classification with an efficient preprocessing technique for cross-language and multilingual data
od: Khan, Towhid, i wsp.
Wydane: (2023)