Terrorism & social mediaWhy the next terror manifesto could be even harder to track
Just before his shooting spree at two Christchurch, New Zealand mosques, the alleged mass murderer posted a hate-filled manifesto on several file-sharing sites. Soon, the widespread adoption of artificial intelligence on platforms and decentralized tools like IPFS will mean that the online hate landscape will change. Combating online extremism in the future may be less about “meme wars” and user-banning, or “de-platforming,” and could instead look like the attack-and-defend, cat-and-mouse technical one-upsmanship that has defined the cybersecurity industry since the 1980s. No matter what technical challenges come up, one fact never changes: The world will always need more good, smart people working to counter hate than there are promoting it.
Just before his shooting spree at two Christchurch, New Zealand mosques, the alleged mass murderer posted a hate-filled manifesto on several file-sharing sites, and emailed the document to at least 30 people, including New Zealand’s prime minister. He also posted on several social media sites links to the manifesto and instructions on how to find his Facebook profile to watch an upcoming video. The video turned out to be a 17-minute Facebook livestream of preparing for and carrying out the first attack on March 15. In his posts, the accused killer urged people to make copies of the manifesto and the video, and share them around the internet.
On March 23, the New Zealand government banned possession and sharing of the manifesto, and shortly thereafter arrested at least two people for having shared the video. By then, the original manifesto document and video file had long since been removed from the platforms where they were first posted. Yet plenty of people appear to have taken the shooter’s advice, making copies and spreading them widely.
As part of my ongoing research into extremism on social media – particularly anti-Muslim sentiment – I was interested in how other right-wing extremists would use the manifesto. Would they know that companies would seek to identify it on their sites and delete it? How would they try to evade that detection, and how would they share the files around the web? I wanted to see if computer science techniques could help me track the documents as they spread. What I learned suggests it may become even harder to fight hate online in the future.
To catch a file
To find as many different versions of the manifesto as possible, I chose an unusual keyphrase, called a “hapax legomenon” in computational linguistics: a set of words that would only be found in the manifesto and nowhere else. For example, Google-searching the phrase “Schtitt uses an unamplified bullhorn” reveals that this phrase is used only in David Foster Wallace’s novel “Infinite Jest” and nowhere else online (until now).
