Study of different machine learning approaches for identification of fake news articles.
Tutor / director / evaluatorVan Wunnik, Lucas Philippe
Document typeMaster thesis
Rights accessOpen Access
In this document multiple machine learning approaches, including Supervised, Semi-supervised and Unsupervised learning are explored with the objective of finding the best algorithm for the task of identifying fake news. The corpus used consists on pure text data extracted from news articles. TF-IDF and word2vec features are studied. Python is used for the implementation