In this project, I extracted +40 leading indicators to forecast the UK inflation rate from Twitter tweets from 2018 to 2022 in the UK for the Data-Driven Economics course in my master's at Sapienza University
README is a tutorial for conducting an Exploratory Data Analysis (EDA) of tweets based on my summer 2022 MnDRIVE Human in the Data Fellowship. Also included is code for an EDA of Aquatic Invasive Species-related tweets that can be adapted to your use case.
A projected aimed at understanding how resources vary in Northern Cape cities or towns to make decisions that influence policy amendments
Python-Flask Web-Application Projects
The Don Elon AI is a twitter sentiment analysis tool. Based on an analysis of over 15'000 different tweets, it is able to categorise tweets and twitter profiles into various different categories. The categories are represented by a string of fictional celebrities, including Don, Elon, AOC, Kylie, Dr. Jordan, and Mia.
An AI Powered Behavioral Analysis Web Application
End-to-end study of EA Sports' FIFA localization
Dashboard of Twitter sentiment analysis
This is the sentiment analysis on the #VisitRwanda on twitter, this is a campaign of eco tourism in Rwanda that promotes touristic places attraction in Rwanda.
Tweet sentiment with MultinomialNB
Sentiment Analysis of Bernie Sanders Tweets for the period: 2020-10-19 to 2021-08-17
Hackathon project by my team for the Truminds AI Hackathon organised ny IIT-B
Análise de sentimentos das postagens mais recentes feitas no twitter (em inglês) que envolvam o termo covid19.
This is an analysis on Black Lives Matter Tweets from Normal People and News Channels using various Unsupervised Natural Language Processing techniques. Tweets starting from 2020-05-25 (death of George Floyd) to 2020-08-01.
Twitter Data Collection, Analysis Tool
SNAPP - Soil Organic Carbon Twitter data
an app that pulls twitter data, analyzes and scores stock tweets with ML based on their sentiment
Sentiment Analysis of Tweets via rtweet
Detecting whether a particular tweet contains negative emotions attached with it or not from the given dataset
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