How we can use machine learning algorithms to prevent cyber stalking?: a review of available empirical evidences and the technology

Cyberstalking has emerged as a significant threat in the digital age. This apparently has led to psychological and financial distress for victims. One can assign this development to the rapid advancement of technology. However, the same technology, in the form of artificial intelligence, machine learning (ML) algorithms and predictive analytics, can also be seen as potential tools to prevent cyberstalking. This clearly seem to be a paradoxical situation, where the solution lies within the problem itself. This paper uses this context to examine, and explore, the empirical evidences and technological advancements in the sphere of AI, ML and Predictive analytics, about how they provide a cyber-shield to cyberstalking. The paper evaluates the effectiveness of supervised, unsupervised, and reinforcement learning models for identifying and preventing cyberstalking behavior on the online platform.