A Survey Of Machine Learning Based Techniques For Hate Speech Detection On Twitter.

Resumo

The use of the internet and social networks, in particular for communication, has significantly
increased in recent years. Twitter is the third most popular worldwide Online Social Network (OSN) only after
Facebook and Instagram. Compared to others OSN’s, Twitter presents a simpler data model and more
straightforward data access API, which makes it a useful tool to study and analyze online behavior, including
abusive patterns. This survey is an attempt to create a machine learning based guide for hate speech automatic
classification including a description of twitter’s technology and terminology, social graphs, sentiment analysis
concepts and hate speech identification. This study also adopted a systematic literature review on the most
advanced computing techniques involved with the subject, focusing on the machine learning state-of-art and
research directions.