review-analysis
There are 40 repositories under review-analysis topic.
VaibhavAbhimanyooHiwase/Sentimental_Analysis_using_Opinion_Target_and_Opinion_Words
This project performed sentimental analysis based on opinion words (like good, bad, beautiful, wrong, best, awesome, etc) of selected opinion target ( like product name for amazon product reviews).
vectornguyen76/QN-Hackathon-CTA-Matrix
Quy Nhon AI Hackathon 2022 - Challenge 2: Review Analytics - Top 1 Solution
fani-lab/LADy
LADy π: A Benchmark Toolkit for Latent Aspect Detection Enriched with Backtranslation Augmentation
apresswala52/Amazon-Fine-Foods-Review-Analysis-and-Modelling
The Amaon Fine Foods Review dataset consists of reviews of fine foods from Amazon. There are approximate 500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. The Aim of this case study was to predict the polarity of the reviews ie. positive/negative. I have applied various Machine Learning Techniques & Algorithms and documented the results accordingly
mintplo/steam-game-review-analysis
Game Review Analysis in Steam for 2019 HYU Social Network Analysis and Text Mining Term Project
alperiox/review-classification-kili-hf-automl
Opinion classification with kili-technology and huggingface by fine-tuning roBERTa model.
AzelyFox/Reviewer
A Simple, Minimal Review Collector
deepankarvarma/Ratings-Prediction-from-Reviews-Using-Classification
This repository contains the code for a rating review classification project that was submitted for the Kaggle Wars competition hosted by ACM Thapar. The project aims to classify reviews based on their rating, using data pre-processing and a convolutional neural network (CNN) model.
JamesLi197412/eCommerce_analysis
Ecommerce analysis
joshivaibhav/AmazonCustomerReview
Analysing Amazon customer reviews via Clustering, Visualization and Classification
krishnavpai/Sentiment-Analysis-Word-Cloud-and-Topic-Modelling-on-customer-reviews-of-FMCG-products-in-India
This project aims to analyze consumer sentiment towards (FMCG) company products by scraping reviews & performing text analysis using Python. By leveraging NLP techniques, such as sentiment analysis, word cloud and topic modelling. The results of this study can inform product development, marketing strategies & overall business decision-making
mingmin0101/Mining-User-Requirements-from-Online-Reviews
2021 Introduction-to-Information-Retrieval-and-Text-Mining Final Project
nayan-pradhan/AmazonReviewAnalysis_NLP
This project uses Machine Learning, Natural Language Processing (NLP), and Web Scraping in order to get real customer reviews for any product on Amazon and perform sentiment analysis that predicts whether the reviews are positive or negative.
rahulgaikwad2010/touch-note-app-review-classification-web-app
An AI solution which cognitively able to detect(classify) reviews in fractions of seconds. hence, fewer human interventions, more precise, uniform results, and most importantly operational efficiency.
techysanjo/AmazonReviews_SentimentAnalysis_FineTune_BERT
A Machine Learning model for sentiment analysis of Amazon reviews that can predict the customer sentiments based on their product reviews
Zhiyu-Lei/Web-Scraping-Customer-Reviews
Extract customer reviews from some online stores and classify negative reviews.
AISHIK999/amazon-review-analyzer-db
Analyse amazon reviews' sentiment and store the data in a mariadb database
AISHIK999/e-commerce-review-analysis
Scrape product reviews from e-commerce sites (Amazon as of now) and perform sentimental analysis on them using LLM and prompt engineering
ali-naderi/User-Review-Analysis-LSTM
The goal of this repository is to predict review rates based of the review text using deep learning (Long Short-Term Memory--LSTM).
GaoDeBuChou/Web-Scraping-Customer-Reviews
Extract customer reviews from some online stores and classify negative reviews.
mujtabaali02/Play-Store-Review-Analysis
Code of Play Store Review Analysis Project, and I gained some valuable insights from the play store dataset.
noorulhudaajmal/BizReview-Analyzer
a Streamlit app that uses the Google Places API to analyze and visualize reviews of various business places across different locations
ornellamariestella/Amazon-reviews-scraping-and-sentiment-analysis
Extracting e-commerce insights and recommendations from Amazon product reviews using sentiment analysis and issue categorization
sayantani-dey/NLP-Analysis-Of-Amazon-Food-Reviews
Sentiment Analysis of Amazon Food Reviews to the customer ratings using VADER, TextBlob and Flair
steffinazareth/ReviewZoid-Python-Project
An application to provide clients with a onestop, centralized platform to gain a snapshot of their company and competitors, financially, among consumers, and in the media.
WISETICT-PPAM/Idea
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yjyuwisely/MovieSense_NLP
MovieSense, an NLP project that provides sentiment analysis, translation, summarization, and text generation services for movie reviews.
Zhiyu-Lei/Amazon-Fine-Food-Review-Score-Prediction
Descriptive and predictive analyses of Amazon Fine Food Reviews dataset.
Armanx200/Amazon-Reviews
π₯ Sentiment Classifier App: Instantly predict whether a review is positive or negative using machine learning! π§ π¬ Built with Logistic Regression, trained on 84K+ reviews, with 91.22% accuracy! π
Armanx200/ChatGPT-Reviews
π₯ Sentiment Classifier App: Instantly predict whether a review is positive or negative using machine learning! π§ π¬ Built with Logistic Regression, trained on 84K+ reviews, with 91.51% accuracy! π
Armanx200/Netflix-Reviews
π₯ Sentiment Classifier App: Instantly predict whether a review is positive or negative using machine learning! π§ π¬ Built with Logistic Regression, trained on 84K+ reviews, with 86.80% accuracy! π
Armanx200/Spotify-Reviews
π₯ Sentiment Classifier App: Instantly predict whether a review is positive or negative using machine learning! π§ π¬ Built with Logistic Regression, trained on 84K+ reviews, with 88.15% accuracy! π
lazyCodes7/SmartScrapes
Get your scrapes in sync
nifleisch/lauzhack-amazon-reviews
Framework for mining and analyzing issues from product reviews and interactive visualisation using plotly dash. Finalist project at Lauzhack 2023.
Shefali-Upadhyaya/BuyAdvisor
The ICDE-BuyAdvisor website is a user-friendly solution to help the buyers decide whether to buy products by evaluating the product reviews for them using web scraping and machine learning techniques. Once the evaluation is completed, the product analysis is shared with the buyer.