Text mining and word analysis

openradarscience.org landing page

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

AI & things

Vader

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

Analyze Tweets Sentiment Using NLP

https://github.com/openradar/oss_weather_radar_vm/archive/master.zip

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.

A test sentiment analyzer using VADER library

Developed a churn prediction system for a bank using data preprocessing, feature engineering, and ML. Applied NLP (tokenization, lemmatization, sentiment analysis) on feedback. Implemented Random Forest and SVM with GridSearchCV for hyperparameter tuning, identifying churn factors.

d'barionleg eo-Rinex converter

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.

Vagrant is a tool for building and distributing development environments.

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.

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.