World Cup Sentiment Analysis and Performance Prediction.
Small project developed for the Reti Geografiche exam in the 22/23 academic year at UNISA.
This project aimed at massively analizing the sentiment score of tweets generated during the 2022 FIFA World Cup held in Qatar, in order to predict the final winner based popular opinion vs actual in-game metrics like aggregated match stats. During the event we gathered millions of tweets everyday, for every match, and we compared the aggregated sentiment score with the matches result for every team.
We used Twitter APIs to gather the results, and a couple of libraries to analyze the data.
The results were used to predict the winner of the final, which was closely predicted. In general the model achieved good results, but it's obviously partial and not meant for serious use.
In the repository you'll find the tweets that we amassed, and some scripts to launch queries on certain hashtags that we found relevant, plus some info on the results and some very basic scripts to automate the retrieval.