Supervised Learning Model for Combating Cyberbullying: Indonesian Capital City 2017 Governor Election Case

Abstract

Technological growth has triggered the internet usage in Indonesia, especially the social media. However, the cyberbullying that is believed has a negative effect on the victims bigger than the traditional one come as a price of this changing trend. It is not an easy task to eliminate or reduce such bad action due to several reasons. Firstly, the cyberbullying often appear in an informal language, slank or local languages. Secondly, the content must be understood from a specific context. In order to have such a tool to combat the cyberbullying, such model and tested algorithm should be made and confirmed by the linguists. This research develops a cyberbullying corpus in order to develop a supervised learning algorithm. The data have been crawled from the social media during the Indonesian capital city 2017 governor election event where the cyberbullying between the candidates supporters occurred. After the data preprocessed and classified by the experts/linguists for the feature space design.