academictwitteR
academictwitteR: an R package to access the Twitter Academic Research Product Track v2 API endpoint - Published in JOSS (2021)
mep
Project MEP: Meme Evolution programme. A terraformed multi-language library to do statistical experiments in Twitter.
search-tweets-python
Python client for the Twitter 'search Tweets' and 'count Tweets' endpoints (v2/Labs/premium/enterprise). Now supports Twitter API v2 /recent and /all search endpoints.
getoldtweets3
A Python 3 library and a corresponding command line utility for accessing old tweets
https://github.com/lromul/gramtion
Twitter bot for generating photo descriptions (alt text)
https://github.com/dcavar/antisemitismdatathon2020
This is project material for the Antisemitism Datathon and Hackathon 2020 at Indiana University
https://github.com/citiususc/polypus
Polypus: a Big Data Self-Deployable Architecture for Microblogging Text Extraction and Real-Time Sentiment Analysis
https://github.com/cabralpinto/wildfire-heat-map-generation
Wildfire Heat Map Generation with Twitter and BERT
https://github.com/hauselin/misinfo-expose-svelte
app for measuring how much misinformation you're exposed to on twitter
https://github.com/ahmedshahriar/depression-tweets-scraper
A Scraper that scrapes '#depression' tweets daily powered by GitHub action and snscrape (stopped at June 30,2023)
https://github.com/atharvapathak/twitter_sentiment_analysis_project
Twitter sentiment analysis is the process of analyzing tweets posted on the Twitter platform to determine the overall sentiment expressed within them. It involves using natural language processing (NLP) and machine learning techniques to classify tweets.
stock-market-prediction-web-app-using-machine-learning-and-sentiment-analysis
Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
twitterfakenet
Classifying Verified used users on Twitter based on how likely they are to share Fake News articles
algorithmic_bias_in_echo_chamber_formation
Computational Social Science Project: "Algorithmic Bias in Echo Chamber Formation".