Title
Predicting Cyberbullying on Social Media in the Big Data Era Using Machine Learning Algorithms: Review of Literature and Open Challenges
Abstract
Prior to the innovation of information communication technologies (ICT), social interactions evolved within small cultural boundaries such as geo spatial locations. The recent developments of communication technologies have considerably transcended the temporal and spatial limitations of traditional communications. These social technologies have created a revolution in user-generated information, online human networks, and rich human behavior-related data. However, the misuse of social technologies such as social media (SM) platforms, has introduced a new form of aggression and violence that occurs exclusively online. A new means of demonstrating aggressive behavior in SM websites are highlighted in this paper. The motivations for the construction of prediction models to fight aggressive behavior in SM are also outlined. We comprehensively review cyberbullying prediction models and identify the main issues related to the construction of cyberbullying prediction models in SM. This paper provides insights on the overall process for cyberbullying detection and most importantly overviews the methodology. Though data collection and feature engineering process has been elaborated, yet most of the emphasis is on feature selection algorithms and then using various machine learning algorithms for prediction of cyberbullying behaviors. Finally, the issues and challenges have been highlighted as well, which present new research directions for researchers to explore.
Year
DOI
Venue
2019
10.1109/ACCESS.2019.2918354
IEEE ACCESS
Keywords
Field
DocType
Big data,cyberbullying,cybercrime,human aggressive behavior,machine learning,online social network,social media,text classification
Data collection,Social media,Feature selection,Computer science,Algorithm,Feature engineering,Artificial intelligence,Information and Communications Technology,Predictive modelling,Big data,Machine learning,Aggression
Journal
Volume
ISSN
Citations 
7
2169-3536
0
PageRank 
References 
Authors
0.34
0
10
Name
Order
Citations
PageRank
Mohammed Ali Al-Garadi11045.69
Mohammad Rashid Hussain200.68
Nawsher Khan3174.53
G. Murtaza4208.55
Henry Friday Nweke5594.57
Ihsan Ali6176.82
Ghulam Mujtaba7508.68
Haruna Chiroma814124.31
Hasan Ali9298.71
Abdullah Gani101068.63