CybercrimeNLP (CC-NLP): A natural language processing toolkit for the interdisciplinary analysis of underground online forums

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Online and electronic crime now account for about half of all property crime, in all countries for which we have good victimisation data. A significant number of other offences, including harassment, also happen online. It is therefore essential for criminologists, lawyers, social scientists, psychologists and others to be able to study online crime and work out what's going on.We are starting to have some really good sources of data, including more than 70 million messages scraped from underground crime forums in the CrimeBB database. There forums are where cyber-crooks meet up, trade tools and techniques, and sell each other services. They are a gold mine for criminologists studying how young people get drawn into crime; social scientists studying the evolution of political ideology, racism and homophobia; lawyers interested in criminal business models and how they respond to police interventions; and many others.The missing link at present is this: that scholars in the humanities and social sciences do not at present have the tools to deal with such large bodies of text. In the pre-Internet era, researchers might have interviewed a few dozen criminals, coded up the interviews by hand and analysed them using a statistics package; but dealing with millions of messages requires new approaches.This project will draw upon the discipline of natural-language processing to build tools that will enable scholars in the humanities and social sciences deal with these large volumes of text using modern techniques of artificial intelligence and machine learning (AI/ML). They will help researchers find topics of interest, identify the types of crime being discussed, search for messages that are similar in various ways to those already identified, track trends, and match users across forums. Users will be able to look for indicators that identify users who are just starting out (and might therefore be targeted with primary prevention approaches) as well as those who are becoming influential (and might therefore be worth more aggressive interventions). Our tools will also enable researchers to measure the effect of both crime-prevention initiatives and policing action, so that policymakers can gather evidence of what works and what doesn't.The tools we build will start to do for research with large text corpora drawn from crime forums, what search engines have done for the Internet -- namely making such resources accessible to researchers who do not have either technical skills or technical assistance. They will therefore enable much more use to be made of existing data resources, starting with the CrimeBB database (which was funded in a previous project funded by ESRC and EPSRC), but not limited to it. Their use by researchers in diverse disciplines will also enable us to learn about how NLP tools, and more generally AI/ML tools, can be used robustly. This is of independent importance given the current rush to use AI/ML techniques and the concern that some of these techniques may simply reflect the bias in their training data, leading naive researchers to just measure their own ruler. It's not enough just to invent new tools; we also have to figure out how to use them properly, and for that, it's vital to work with a community of scholars from multiple disciplines in the humanities and social sciences on a shared problem, using shared data, and where we have some access eventually to ground truth.