Text mining and word analysis

Vader

This project is about how we analyze sentiment of the written text/sentence

Materials for Sentiment Analysis with Python in "Taller en Data Science" by UCOM

Analyze Tweets Sentiment Using NLP

This Python script is designed for algorithmic traders

This is a Natural Language Processing Project using VADER, Afinn, Textblob, Transformers and ML model. Also using Flask.

A test sentiment analyzer using VADER library

VADER takes a traditional sentiment analysis approach using a pre-built lexicon scoring while taking into account negation and intensity; however, it is only limited to the provided lexicon. RoBERTa on the other hand is state of art transformer-based language model that has high performance with the ability to analyze contextual information.

Popularity and Controversy: A Location-Based Event and Sentiment Analysis of Donald Trump and Boris Johnson

Updated replacement for vader-sentiment (vaderSentiment-js) that runs original vaderSentiment natively, using CPython.

Sentiment analysis on Twitter comments using machine learning and NLP. Collects data through Twitter API, processes text with VADER for sentiment classification, trains Logistic Regression model, and saves results to CSV.

Sentiment Analysis using nltk vader package - Rule based classifier

Sentiment analysis

This repository contains a project focused on performing sentiment analysis on the Amazon Fine Food Reviews dataset. The goal is to analyze customer reviews to determine their sentiment, whether positive or negative, and to gain insights into customer opinions to improve product offerings.

Analyzing sentiment in Spotify music dataset using natural language processing

Apply news sentiments to graph word clouds for most popular words in Bitcoin and Ethereum articles. Named entity recognition is carried out with color-coded tags in SpaCy.

a stateless web app that leverages sentiment analysis models to plot the vibe of tweeters over time