Sentiment Analysis of 1.72 million tweets regarding Joe Biden and Donald Trump from 2020 US election to find political trends and predict election outcome.

Toolset for checking differences in recognising semantic relation presence by: (1) large language models 🤖 and (2) annotators / experts ✍️

The Product Review Sentiment Analysis project that leverages NLP and ML techniques to classify customer reviews into positive, negative or neutral sentiments. The application provides insights into customer feedback, helping to identify product strengths and weaknesses and enhance the overall customer experience.

A compassionate and supportive chatbot designed to provide users with emotional support and encouragement. Utilizing advanced sentiment analysis powered by Hugging Face's AI

Sentiment Analysis using Hugging face transformers

Conducted sentiment analysis on Amazon reviews using natural language processing techniques and Transformers model to classify reviews as positive, negative, or neutral.

Directory for Reddit API (praw) ETL process. This particular analysis is designed for the financial industry but can be modified to include any subreddit or group of subreddits from Reddit's platform. Incorporates the VADER and FinBERT sentiment analysis models. Additional querying and visualization done in Power BI.

This repository provides examples for using the FreeGPT module, a lightweight Python library for integrating GPT (Generative Pre-trained Transformer) capabilities into various applications. These examples demonstrate how to leverage FreeGPT for a range of tasks.

Text Mining, Sentiment Analysis, Statistical Analysis

NLP Techniques on comedy corpora

"Detect sarcasm effortlessly! This Python app uses NLP and ML to analyze text sentiment, distinguishing sarcastic tones. With a user-friendly interface, input any text for real-time sarcasm identification. Achieve accurate results through advanced sentiment analysis techniques and trained models."

Todo lo accesorio y entorno al proyecto sobre Análisis de textos con R

Explore Dutch Social Media trends with analyses on influencer behavior, geographical insights, daily activity patterns, sentiment trends, and prevalent topics using Python.

Analyzes emotions in text chunks per chapter using a sentiment analysis model, visualizing scores across chunks as line graphs. Includes pie charts showing dominant emotions per chapter, enhancing understanding of emotional variations in text chunks. Developed using Transformers library.

A project that harnesses the Stanford NLP library to gauge sentiment from provided text via an intuitive graphical interface.

An implementation of ABSA

The goal of sentiment analysis is to classify the text based on the mood or mentality expressed in the text, which can be positive negative, or neutral.