JavaScript port of VADER sentiment analysis tool

Sentiment Analysis of tweets about car manufacturers. Complete Docker Pipeline with ETL job that is managed through Airflow.

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.

Twitter Sentiment Analysis Using Vader Lexicon and Random Forest Classifier

This is a collection of Jupyter notebooks that use popular sentiment analysis Python libraries to analyze text.

VaderSentiment is implementation of VADER sentiment analysis tool in Julia language.

Prediction Stock price using News Sentiment and Other Major Index like S&P 500 and Nikkei 225 Index.

This Python code retrieves thousands of tweets, classifies them using TextBlob and VADER in tandem, summarizes each classification using LexRank, Luhn, LSA, and LSA with stopwords, and then ranks stopwords-scrubbed keywords per classification.

Vanilla client-side version of Python's VADER sentiment snalysis tool

anime quotes classification and sentiment analysis

Learning streamlit as a dashboard and viz tool for data science projects

Sentiment Analysis and Word Count of Feedbacks using Apache Spark

Sentiment Analysis on Twitter Tweets.

Text mining and sentiment analysis.

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++.

A simple web app that determines whether a piece of code is positive,neutral or negative in mood using python

Simple webapp that analyzes the sentiment of text files in a diary folder and visualizes the positivity and negativity trends over time.

Due to the size restriction the dataset file is unable to upload but you can simply download from kaggle.