Amazon product reviews sentiment analysis using supervised learning algorithms

Amazon product reviews sentiment analysis using supervised learning algorithms

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliografiska uppgifter
Huvudupphovsmän:	Hawladar, Mohibullah, Ghosh, Arjan, Raad, Zaoyad Khan, Chowdhury, Wali Ahad, Shehan, Md Sazzad Hossain
Övriga upphovsmän:	Ashraf, Faisal Bin
Materialtyp:	Lärdomsprov
Språk:	English
Publicerad:	Brac University 2021
Ämnen:	Sentiment Analysis Opinion Mining Amazon Review Analysis Support Vector Machine (SVM) Decision tree Logistic Regression MLP Random Forest Analysis Sentiment analysis.
Länkar:	http://hdl.handle.net/10361/14970

Liknande verk

Aspect-based sentiment analysis using SemEval and Amazon datasets
av: Hasib, Tamanna, et al.
Publicerad: (2018)

Sentiment analysis for Bengali newspaper headlines
av: Hossain, Mohammad Samman, et al.
Publicerad: (2017)

Sentiment analysis on mobile operators’ customer review
av: Hossain, Mohammed Mohibul, et al.
Publicerad: (2020)

Predicting stock market movement using sentiment analysis of twitter feed
av: Chakraborty, Pranjal, et al.
Publicerad: (2017)

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

An advanced hospital rating system using machine learning and natural language processing
av: Tamjid, Ali Asgar, et al.
Publicerad: (2023)

A machine learning approach to predict movie box-office success
av: Quader, Nahid, et al.
Publicerad: (2018)

Analyzing users’ sentiment towards video games based on reviews from microblog
av: Roy, Abhijeet, et al.
Publicerad: (2018)

Analyzing data of social media to evaluate customer behavior of companies using sentiment analysis
av: Shourin, Bushra, et al.
Publicerad: (2018)

Sentiment analysis using R: an approach to correlate bitcoin price fluctuations with change in user sentiments
av: Rahman, Shaomi, et al.
Publicerad: (2018)

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

A multimodal approach of sentiment analysis to predict customer emotions towards a product
av: Islam, Shadman, et al.
Publicerad: (2020)

Performing sentiment analysis in Bangla microblog posts
av: Chowdhury, Shaika, et al.
Publicerad: (2017)

Analysis on the effects of wallstreetbets on the stock market
av: Hossain, Abir, et al.
Publicerad: (2022)

Optimizing restaurant recommendations through sentiment analysis
av: Juha, Tasnia, et al.
Publicerad: (2024)

Microblog sentiment analysis for rating TV shows
av: Abdullah, Ashik
Publicerad: (2017)

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

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

Social media trend analysis to predict the success of products using deep learning technique
av: Khan, Farden Ehsan, et al.
Publicerad: (2023)

Predicting stock market trend from twitter feed and building a framework for Bangladesh
av: Karim, Shabab, et al.
Publicerad: (2018)

Text classification with an efficient preprocessing technique for cross-language and multilingual data
av: Khan, Towhid, et al.
Publicerad: (2023)

A voice signal based gender prediction model using random forest classifier
av: Ahmed, Saif, et al.
Publicerad: (2018)

Heart disease prediction system
av: Amit, Tayab Al Azad, et al.
Publicerad: (2022)

Feature based mobile phone rating using sentiment analysis and machine learning approaches
av: Kafi, Abdullahil, et al.
Publicerad: (2018)

Product rating generation based on public opinion using sentiment analysis
av: Rabbi, Reshan Ahmed, et al.
Publicerad: (2018)

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

Sentimental analysis of customer product Reviews to understand customer needs using machine learning
av: Symum, Md Abdullah Al, et al.
Publicerad: (2023)

Embedded system based bangla intelligent social virtual robot with sentiment analysis
av: Hossain, Md. Ishan Arefin, et al.
Publicerad: (2018)

Sentimental analysis on political speeches
av: Atiq, Asif, et al.
Publicerad: (2022)

A framework for sentiment analysis: a data-driven approach
av: Islam, Md. Jahedul, et al.
Publicerad: (2021)

Forecasting bitcoin price considering macro economic factors and media influence using bidirectional LSTM and random forest regressor as ensemble model
av: Ghose, Swattic, et al.
Publicerad: (2023)

A supervised learning approach by machine learning and deep learning algorithms to predict type II DM risk
av: Farabe, Abdullah Al, et al.
Publicerad: (2021)

A deep learning approach to predict crypto-currency price by evaluating sentiment and stock market correlations
av: Maliha, Miftahul Zannat, et al.
Publicerad: (2023)

Prediction of bipolar disorder from mental episodes using machine learning approach
av: Tasmeem, Sumaiya, et al.
Publicerad: (2023)

Sentiment analysis of customer reviews on food ordering portals of Bangladesh using natural language processing
av: Deb, Priom, et al.
Publicerad: (2024)

Share market forecasting with LSTM neural network and sentimental trend prediction
av: Rony, Ismail Hossain, et al.
Publicerad: (2020)

Sentiment classification on Bengali food and restaurant reviews
av: Hossain, Abid, et al.
Publicerad: (2024)

Supervising vehicle using pattern recognition
av: Lushan, Mihodi Hasan, et al.
Publicerad: (2018)

Sentiment analysis in Bengali Text using NLP
av: Sarkar, Ankon, et al.
Publicerad: (2023)

A machine learning approach to analyze and predict rainfall in different regions of Bangladesh
av: Rahee, Arnob, et al.
Publicerad: (2021)