A python package for classifying emotion

NLP project on "The Silmarillion" by J.R.R. Tolkien. Text and sentiment analyses using NLTK, VADER, Text Blob, and NRC Emotion Lexicon.

Análisis de sentimientos y visualización de datos con R, de conversaciones de WhatsApp, segunda parte. Uso de librería rwhatsapp.

Sentiment Analysis in Javascript using the various lexicons including AFINN-165, VADER, NRC Word-Emotion Association, Bing and Loughran-McDonald

Content-based +Emotion/Mood aware Music Recommendation system

Applications of NLP like Topic Modeling, Sentiment Analysis, Word Cloud along with Web Scraping.

this repo contains files for my analysis on disney land visitor reviews using NLP

This project uses machine learning to categorize and prioritize airline user tweets based on content and sentiment. The goal is to reduce airlines' workload and provide personalized, empathetic responses to users. By training a sentiment analysis model, airlines can better understand customers' needs and improve their overall service on Twitter.

Extract Video Game reviews from IGN's website using Beautiful Soup then apply Sentiment analysis using 3 pre-trained models including Hu and Lui, Vader and NRC

A content based recommendation system for Taylor's recent albums

Developed an Automated Twitter Response Tool for a focus in airline complaints using Kafka Streaming, LSTM, LDA, NRC Lexicon, and made analysis reports by using dataprep.ai

Sentiment Analysis on “HelloTalk” App Review Data with NRC Emotion Lexicon and GoEmotions Dataset

Sentiment Analysis of the European Commission Report (2012, 2015, 2018) with Several Emotion Dictionaries and a ShinyDashboard

In the present day, the entertainment industry is constantly evolving toward making the most enjoyable and profitable sources of film entertainment. Through the use of movie rating sites, we can now decide whether or not it is worth the trip to the movie theatre to watch a partiuclar film. With this in mind, I wanted to explore what aspects of m…

Practical work framed and developed in the course of Environmental Intelligence : Technologies and Applications

This project analyzes and compares the Wikipedia articles of Xi Jinping and Vladimir Putin over 20 years, uncovering differences in portrayal, sentiment, and biases to measure public perception of each leader.

This project aims to understand the sentiment when a bit policy is introduced by the government. I have used Twitter data to do sentiment analysis using R.

The system is implemented to scrape data from a booking website, perform Emotion Analysis on the reviews of the selected hotel and visualized the result over a time axis. R is used to implement the system and Shiny library is used to develop the Front-end.

Programming for Social Science, 2021

codes for: "Applications of social-media mining in examining the social concerns of orphans during the early stages of the COVID-19 pandemic."