Sentimental analysis of customer product Reviews to understand customer needs using machine learning

Sentimental analysis of customer product Reviews to understand customer needs using machine learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Библиографические подробности
Главные авторы:	Symum, Md Abdullah Al, Sheemu, Subarna Yeasmin, Asif, Abu Saleh Md., Islam, Konika
Другие авторы:	Shakil, Arif
Формат:	Диссертация
Язык:	English
Опубликовано:	Brac University 2023
Предметы:	Natural language processing Customer feedback Textual data analysis Sentimental analysis Transformer Sentiment lexicons Word embeddings Machine learning Natural language processing (Computer science)
Online-ссылка:	http://hdl.handle.net/10361/21980

Схожие документы

Sentiment analysis on mobile operators’ customer review
по: Hossain, Mohammed Mohibul, и др.
Опубликовано: (2020)

Human sentiment analysis using natural language processing
по: Shamya, Md. Shamiul Haque Khan, и др.
Опубликовано: (2024)

Sentiment analysis in Bengali Text using NLP
по: Sarkar, Ankon, и др.
Опубликовано: (2023)

Sentiment analysis using R: an approach to correlate bitcoin price fluctuations with change in user sentiments
по: Rahman, Shaomi, и др.
Опубликовано: (2018)

A transformer based approach to detect the sentiment of drivers in ride sharing platforms
по: Chakraborty, Sovon
Опубликовано: (2024)

A multimodal approach of sentiment analysis to predict customer emotions towards a product
по: Islam, Shadman, и др.
Опубликовано: (2020)

Optimizing restaurant recommendations through sentiment analysis
по: Juha, Tasnia, и др.
Опубликовано: (2024)

Sentiment analysis of customer reviews on food ordering portals of Bangladesh using natural language processing
по: Deb, Priom, и др.
Опубликовано: (2024)

Microblog sentiment analysis for rating TV shows
по: Abdullah, Ashik
Опубликовано: (2017)

Sentiment classification on Bengali food and restaurant reviews
по: Hossain, Abid, и др.
Опубликовано: (2024)

Embedded system based bangla intelligent social virtual robot with sentiment analysis
по: Hossain, Md. Ishan Arefin, и др.
Опубликовано: (2018)

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

Aspect-based sentiment analysis using SemEval and Amazon datasets
по: Hasib, Tamanna, и др.
Опубликовано: (2018)

Analyzing data of social media to evaluate customer behavior of companies using sentiment analysis
по: Shourin, Bushra, и др.
Опубликовано: (2018)

Analyzing users’ sentiment towards video games based on reviews from microblog
по: Roy, Abhijeet, и др.
Опубликовано: (2018)

Sentiment analysis for Bengali newspaper headlines
по: Hossain, Mohammad Samman, и др.
Опубликовано: (2017)

Comparative study of toxic comments classification using machine learning algorithms
по: Razzak, Razia, и др.
Опубликовано: (2021)

Social media sentiment study on COVID-19 outbreak
по: Karmaker, Anik, и др.
Опубликовано: (2021)

BWN- A software platform for developing Bengali wordnet
по: Khan, Mumit, и др.
Опубликовано: (2010)

Research report on Bengla tagged lexicon
по: Hayder, Kamrul, и др.
Опубликовано: (2010)

Amazon product reviews sentiment analysis using supervised learning algorithms
по: Hawladar, Mohibullah, и др.
Опубликовано: (2021)

Product rating generation based on public opinion using sentiment analysis
по: Rabbi, Reshan Ahmed, и др.
Опубликовано: (2018)

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

A rule based approach for implementation of bangla to english translation
по: Rahman, Md. Khalilur, и др.
Опубликовано: (2017)

Feature based mobile phone rating using sentiment analysis and machine learning approaches
по: Kafi, Abdullahil, и др.
Опубликовано: (2018)

Virtual teaching assistant for undergraduate students using natural language processing & deep learning
по: Sakib, Sadman Jashim, и др.
Опубликовано: (2023)

Research report on Bengla lexicon
по: Hayder, Kamrul
Опубликовано: (2010)

Screencast feedback versus textual feedback in L2 writing: an experimental study on IELTS writing task 2 responses in the Bangladeshi context
по: Neon, Muhaiminul Islam
Опубликовано: (2023)

Market demand analysis using NLP in Bangla language
по: Hossain, Md Sabbir, и др.
Опубликовано: (2022)

Sentimental analysis on political speeches
по: Atiq, Asif, и др.
Опубликовано: (2022)

Performing sentiment analysis in Bangla microblog posts
по: Chowdhury, Shaika, и др.
Опубликовано: (2017)

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

A framework for sentiment analysis: a data-driven approach
по: Islam, Md. Jahedul, и др.
Опубликовано: (2021)

TikNep: content analysis of Nepali TikTok users using natural language processing
по: Dhakal, Aakar, и др.
Опубликовано: (2024)

Share market forecasting with LSTM neural network and sentimental trend prediction
по: Rony, Ismail Hossain, и др.
Опубликовано: (2020)

Curious learner: a generative neuro-symbolic approach for function execution & illustration using natural language
по: Joaa, A.F.M. Mohimenul
Опубликовано: (2024)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
по: Maliha, Miftahul Zannat, и др.
Опубликовано: (2023)

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

Bang-lish sentiment classification using deep learning
по: Saleheen, Abrar, и др.
Опубликовано: (2023)

Sentiment analysis on Bangladesh airlines review data using machine learning
по: Hasib, Khan Md.
Опубликовано: (2022)