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VADER Sentiment Analysis Tool with C++. Valence Aware Dictionary and sEntiment Reasoner (VADER) is a lexicon and rule-based sentiment tool designed to measure sentiment of text from social media. Originally written in Python, this is a port to C++.
Fully autonomous and intelligent platform to detect, monitor and manage potholes issues. An end-to-end system with a PWA front-end for users to report potholes and government authorities to track and manage them.
Instagram and Threads are two major social media platforms that are widely used worldwide. Considering the prevalence of social media in today's world, the sentiment surrounding such platforms is of relevance when studying societal trends and patterns.
Data Manipulation project with Python to scrape Facebook and Tesla news headlines, in conjunction with sentiment analysis using NLTK and VADER to generate investment insight.
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.
LeIA (Léxico para Inferência Adaptada) é um fork do léxico e ferramenta para análise de sentimentos VADER (Valence Aware Dictionary and sEntiment Reasoner) adaptado para textos em português.
This is a Python-based project that performs natural language proccessing to get sentiment analysis of Reddit comments using the Vader model and PRAW (Python Reddit API Wrapper) to get data from Reddit.