Classification of Cyberbullying in Facebook Using Selenium and SVM

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Kim D. Gorro, Mary Jane G. Sabellano, Ken Gorro, Christian Maderazo, Kris Capao

2018 2018 3rd International Conference on Computer and Communication Systems, ICCCS 2018 Conference paper Cited by 10 Quartile

Abstract

Cyberbullying is one of the emerging problems over the past few years especially to teenagers. Approximately 24% of teens goes online constantly, facilitated by the widespread availability of smartphones. Almost 21% of teens said the main reason they checked social media always was to make sure nobody was saying mean or bad things to them. Cyberbullying related Facebook posts were harvested by a customized web scraper tool. These harvested data were used for classification using Support Vector Machines (SVM) model. A total of 2263 data was used for training data, Facebook posts. Based on these posts, the study achieved the precision of 88% and the recall is 87%. © 2018 IEEE.

Affiliations

Department of Computer and Information Sciences, School of Arts and Science, University of San Carlos, Philippines