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

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

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…

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 comprehensive Python toolkit that leverages local Large Language Models (LLMs) via Ollama to analyze Steam game reviews.

Sentique is a full‑stack feedback analytics platform that ingests user reviews from App Store, Google Play, Trustpilot, Reddit and Twitter/X, processes them with a fine‑tuned BERT model into 16 categories and sentiment labels, and provides comprehensive analytics and insights.

An AI project developed by interns Nehal, Huzzaifa, and Romman, under the mentorship of Firoz Shaikh, Head of AI Team at Nexgeno.

A Simple, Minimal Review Collector

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

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

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

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

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

AI-powered sentiment analysis tool for evaluating processes and tracking feedback. Extract positive insights from reviews, customer feedback, and text data with real-time analysis and visualization.

AI-powered tool that extracts pros, cons, summary, and sentiment from product reviews using the DeepSeek-Prover-V2-671B model via a Streamlit interface.

An AI-powered system for automated academic peer review. Upload a PDF, and the assistant analyzes novelty, plagiarism, factual accuracy, claim mapping, and citation quality (via GROBID). Includes an optional Deep Search mode to fetch and index new papers for comparison

Ecommerce analysis

Transform Product Reviews into Strategic Market Insights