51猎奇入口

Francesco C. Campisi is a postdoctoral fellow working under the supervision of Professor Richard Frank. His research examines how extremist groups and social movements use social media to recruit members, spread ideologies, and organize. Using computational tools, he maps digital networks and analyses how platforms can help radical content reach more people. His work aims to better understand the impact of such content on online audiences and to identify ways to respond to digital violence and online hate.

What inspired you to study computational criminology, digital extremism, and online mobilization?

My first love interest was to test whether street gangs recruit online. It was one of the main focuses of my master鈥檚 thesis. Subsequently, I moved on to how other groups recruit online, from hacktivist groups like Anonymous to conspiracy theorists like QAnon. With greater knowledge of the subject, I shifted away from binary terms like 鈥渞ecruitment鈥� and began using more appropriate terms for digital spaces, such as 鈥渋nfluence鈥� and 鈥渕obilization鈥�. With the global rise in authoritarianism and far-right extremist ideologies these last few years, I鈥檝e seen a need for a renewed interest in studying the online mobilization practices of extremist groups. While the concepts may change names, the goal has remained the same over the years.

What will you be working on during your fellowship?

During my fellowship, I will be working on an SSHRC-funded project titled "Unmasking Stochastic Terrorism in Canada." This research focuses on detecting and analyzing diverse forms of online hate content within gender-related political discourse. My goal is to use computational analysis to better understand how online hate speech can increase the likelihood of unpredictable, real-world violence.

During your fellowship, you鈥檒l analyze diverse forms of online hate content within gender-related political discourse. Can you tell us more about this project and the questions you hope to answer?

Using conversations from the White Nationalism (WN) forum Stormfront, our goal is to review the role of women in the progression of WN ideology and practices. Which is just a fancy way of saying, 鈥渨e want to see how women recruit other women into actively participating with WN鈥�. This is one鈥攊n what I鈥檓 hoping is a small series鈥攐f articles examining the role of different sociodemographic markers in online (and potentially offline) mobilization. In parallel, I鈥檓 working with a collaborator at Notre Dame University to analyze the role of online religious rhetoric in advocating for violence among White Nationalists, though we are looking to expand this inquiry outside WN and include other forms of far-right extremism.

What are some of the biggest challenges you鈥檝e faced when studying digital communities?

One of the biggest challenges is that they don鈥檛 just provide the information you need for a proper analysis! If they would just post a guidebook of their recruitment practices, my job would be a whole lot easier. Instead, we, as researchers, must use our informed intuition to guess at their intentions and motivations. Similarly, it is incredibly difficult to measure nebulous concepts like online recruitment and influence. As such, we must use a multitude of diverse metadata forms as proxies for mobilization. It takes a great deal of creativity and adaptability to study these digital communities. It鈥檚 like playing chess in the dark.

What drew you to join the School of Criminology for your postdoctoral fellowship, and what excites you about it?

Firstly, 51猎奇入口has a phenomenal reputation as a research institution. I believe Maclean鈥檚 University ranking just recently ranked 51猎奇入口as the #1 comprehensive university in Canada, and it is one of the top universities for innovative criminological research. But beyond these metrics, I was initially drawn by Dr. Richard Frank, professor at 51猎奇入口and Director of the International CyberCrime Research Centre (ICCRC). As a rigid student of the social sciences, I never formally studied computer science for data analysis and, to this day, am largely self-taught. This comes with many limitations. With this postdoc, I plan to learn a great deal from Richard. From data mining techniques to more comprehensive and diverse forms of computational analysis. That鈥檚 what I am most excited about.

Are there any opportunities within the School of Criminology with faculty, students or research centres that you are looking forward to exploring?

Outside of my main focus, I think I鈥檓 mostly looking for a reason to work with Dr. Martin Bouchard, Director of the School of Criminology and the Illicit Network Laboratory at SFU. A part of my master鈥檚 thesis employed social network analysis to examine patterns in gang members鈥� social media presence. Although it remains unpublished, I would love to continue to explore street gangs鈥� use of social media through the lens of network analysis. If ever Martin is reading this answer and is open to exploring the online networks of Canadian street gangs, my door is always open!

For students interested in pursuing similar research interests like yours, such as computational criminology and digital extremism, what skills or perspectives do you think are most valuable today?

Learning from my mistakes, students interested in pursuing computational criminology will benefit from taking courses (if not, full degrees) in computer science. Learning to code鈥攚hether in R or Python鈥攊s invaluable in this field. Programs like SPSS are good for beginners as they offer structured processes for quantitative analysis, but they鈥檙e too inflexible. Consequently, you are limited by the program's constraints. Learning to code is like bending the rules of reality: it imposes very few limitations on data analysis. When I began my master's, I manually coded a couple of hundred posts, which took me over a month. Now, I run analyses across hundreds of thousands of posts at the blink of an eye. For those interested in computational criminology and quantitative analyses, coding is a must.