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).

Quy Nhon AI Hackathon 2022 - Challenge 2: Review Analytics - Top 1 Solution

LADy 💃: A Benchmark Toolkit for Latent Aspect Detection Enriched with Backtranslation Augmentation

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 Le…

Game Review Analysis in Steam for 2019 HYU Social Network Analysis and Text Mining Term Project

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.

A Simple, Minimal Review Collector

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

Opinion classification with kili-technology and huggingface by fine-tuning roBERTa model.

A Machine Learning model for sentiment analysis of Amazon reviews that can predict the customer sentiments based on their product reviews

2021 Introduction-to-Information-Retrieval-and-Text-Mining Final Project

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.

💬 It uses NLP techniques to classify reviews as positive, neutral or negative, providing valuable insights into customer feedback.

Extract customer reviews from some online stores and classify negative reviews.

Ecommerce analysis

Analysing Amazon customer reviews via Clustering, Visualization and 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.

Framework for mining and analyzing issues from product reviews and interactive visualisation using plotly dash. Finalist project at Lauzhack 2023.

🔥 Sentiment Classifier App: Instantly predict whether a review is positive or negative using machine learning! 🧠💬 Built with Logistic Regression, trained on 84K+ reviews, with 91.22% accuracy! 🚀

Review Analysis (NLP) of musical instrument reviews from the amazon dataset. Observing performances of Linear SVC, NaiveBayes (MultinomialNB) , Random Forest Classifier and Logistic Regression under use of Count and tf-idf vectorizers.