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- Sentiment Analysis - Data Mining - Hate Speech - Fake News - Complex Networks
Sentiment Analysis of Twitter Users Who Publish Texts on Politics Over an Election Period: This is part of my master thesis' research. We are characterizing users' sentiments, mood variation, and language patterns of users that published tweets about 2017 American Presidential Election. I identified four user communities using data mining techniques: Trump's Advocates, Hillary's Advocates, Political Bots and Regular Users.
Characterizing Harmful Speech on WhatsApp Public Groups: We are proposing a process to automatically collect data from WhatsApp public groups to perform harmful speech characterization in the messages.
Characterizing User Communities and their Political Homophily in Twitter during the 2016 American Presidential Election: This is part of my master thesis' research. We are characterizing users communities on Twitter (Trump's Advocates, Hillary's Advocates, Political Bots and Regular Users) and their political homophily in uniplex and multiplex connections networks.
Linkedin: http://linkedin.com/in/josemar-a-caetano-8a0483a3
GitHub: https://github.com/josemarcaetano