super_raptor

Digital Forensic Linguistics (DFL) was inspired by forensic linguistics efforts used to help law enforcement apprehend the infamous criminal known as the Unabomber. With new technology available, new kinds of crime have developed which are in the forefront of popular consciousness following such events as the DNC hacking and the 2014 iCloud hack, among others. In these events, the anonymity of the digital presence has led to negative repercussions. Certainly, such anonymity is a cornerstone of positivity as well, allowing persons voices who would otherwise be persecuted. However, as the previous events have shown, the ability to accuse a perpetrator is still exceedingly difficult. DFL allows for criminal profiling by utilizing hundreds of GitHub profiles and scanning for various linguistic features (spaces or tabs, programming languages used, usage of reserved words, etc.) and tagging them to particular demographics either offered by GitHub (such as location) or mined using Microsoft Azure's face API (age and gender, for example). Machine learning tactics are used to spot any correlations of variation between these patterns so that untagged data could use the same models when demographic data is not available (as is the case with malicious code). Although it is still in its fledging stages, super_raptor believes that this technology could be used to make huge strides in the effectiveness of digital criminology.

super_raptor was formed in 2018 by Charles Kronk following placing in the RevolutionUC Hackathon with his project Digital Forensic Linguistics (DFL). The team is comprehensively focused on incorporating "two-fer" philosophy pioneered in such applications as Duolingo and reCAPTCHA (both projects having been started by Carnegie Mellon professor Luis von Ahn). With this in mind, Charles' background includes several applications which he is actively developing on his GitHub (such as biomedical ontology organizer GNOMICS), as well as former applications (such as pharmaceutical dispenser RxMagic).