VaderSentiment is implementation of VADER sentiment analysis tool in Julia language.
In this notebook, I attempted to create a script that utilizes pre-trained CamemBERT and VaderSentiment models to label the sentiment of a Quran Karim dataset in English and French. My goal was to accurately classify the sentiment of each text sample in the dataset.
A Digital Vibe Checker for YouTube, developed by Ananya. This Python tool automates comment extraction via Google API and performs sentiment analysis using NLTK VADER. Generates a visual dashboard (Pie, Bar, Scatter, Time Series) to track community mood vs. engagement. Includes secure .env handling pagination for large datasets and CSV data export.
A real-time sentiment analysis tool that tracks public opinion about any topic by collecting and analyzing posts from Reddit and Hacker News
A data-driven NLP project leveraging machine learning and text analytics to uncover operational bottlenecks and customer sentiment in Starbucks reviews.
A Natural Language Processing project to determine what Bernie supports might do in 2020
Detects psychological manipulation vectors in text. Maps social engineering tactics to cognitive biases using VADER NLP + MITRE ATT&CK framework.
A Django-based web application that fetches Instagram posts via the Graph API and performs real-time sentiment analysis using VADER NLP.
News sentiment analysis: multi-model NLP (FinBERT, VADER, TextBlob) with Prophet forecasting and real-time multi-source aggregation.
Automated drug adverse event analysis pipeline — REST API ingestion, NLP (TF-IDF + VADER), and Streamlit dashboard on 10K+ OpenFDA records
Updated replacement for vader-sentiment (vaderSentiment-js) that runs original vaderSentiment natively, using CPython.
Continuous pain-point discovery from Reddit — fetch, sentiment-filter, LLM-extract, dedup, accumulate.
A Python-based system that analyzes market sentiment from news sources to generate trading signals. Combines NLP (VADER & BERT) with technical indicators to identify trends in commodities and indices (Gold, Oil, S&P 500, Nasdaq).
Predicting which software tickets will stall by analysing the sentiment of developer email discussions around them. Apache Hadoop dataset, 2018–2024.
A Python-based NLP pipeline designed for Customer Operations. This tool automatically processes raw customer reviews and categorizes them into actionable business insights, isolating high churn risks and prioritizing feature requests.
Airflow + PostgreSQL + Spark pipeline scoring 1.78M Airbnb review texts with VADER sentiment. Local[*] Spark, broadcast-joined enrichment, 17 unit tests.
AI-powered sentiment analysis web app with a Logistic Regression + VADER dual-engine classifier, active MLOps retraining, and batch CSV analytics. Dockerized and deployed on Render.
Scores media content across 7 psychological engagement dimensions. Maps Seligman, Cialdini, Russell, Loewenstein, and Kahneman frameworks to content strategy signals.
A Flask web app that analyzes sentiment in news articles and generates word clouds to visualize emotional trends in current events
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