A Framework for Cybercrime Prediction on Twitter Tweets Using Text-Based Machine Learning Algorithm
Sheila Marie M. Matias, Jefferson A. Costales, Christian M. De Los Santos · 2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI) · 2022
With the rise in popularity, social media platforms such as Twitter are more recognized for calling tweets to construct user networks that can communicate. Because of the increasing number of Twitter users and the expansion in cybercrime rates. Cybercrime is a crime perpetrated using technology. It is feasible that the social networking platform might be utilized to commit a crime. The researchers focused on cyberbullying and cyberthreat, given the severity of cybercrime's effects on victims and given the devastating effects of cybercrime on victims, it is critical to devise effective methods for predicting and preventing it. Made advantage of the Twitter API and the tweepy python module to extract a real-time tweet from Twitter. In order to improve their ability to detect cybercrimes and sentiments, through employed an online source dataset to build a model. The goal of this study is to create a machine learning strategy for anticipating cybercrimes. Find the approach that best fits the data by comparing it to other methods. To evaluate the accuracy and dependability of the trained model, through gathered data and information from dependable sources. The significance of the research is shown by the analysis of the data.