Hoax Detection On Twitter

Titi Widaretna, Jimmy Tirtawangsa, Ade Romadhony

Abstract

Abstract—In this paper, we present our work on hoax
detection on a collection of Tweets. We tackle the hoax
detection as a text classification problem, with Doc2Vec as the
text representation method and SVM as the classifier. We
collected and annotated 5000 Tweets that consist of 2500 hoax
Tweets and 2500 truth Tweets. The experimental results show
that the accuracy of our proposed hoax detection on Tweets is
93.4%.
Index Terms—Hoax Detection, Natural Language
Preprocessing

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