Digifesto

One topic I’m interested in researching is the automated detection of certain kinds of social (or anti-social) activity on the internet. This paper. “Visualizing the Signatures of Social Roles in Online Discussion Groups”, by Welser et al., is a good example of a stab at the problem. Can we look at data from a mailing list and identify the most helpful person on it? Welser thinks so, and they develop a preliminary model for detecting them.

That’s all well and good until the roles get more complicated. A great way to make things more complicated is by introducing an adversarial relationship into the mix. The internet is rife with adversity, in the form of flame warriors, trolls, and spammers. There is also much more benign disagreement as well, but this is probably comparatively rare. Or (this is a broad claim based in cynicism, not research:) people are so likely to take disagreement and conflict personally or dismissively that much legitimate conflict on the Internet is probably seen as flaming, trolling, or spamming.

The problem is that it is very hard to pin down the definitions of these terms. This isn’t just a conceptual problem. It’s also a problem for engineering solutions around these roles. Spam filtering, for example, depends on a certain model of what counts as spam. While training a classifier based on a user’s subjective classification makes lots of sense in some circumstances (like a mail filter), in other cases the line may be less clear. Trolling, meanwhile, can be death to a web-based community. Once could argue that Pinterest has only been successful partly because it has been able to keep the trolls out. But in other contexts, where vigorous debate is encouraged, standards of ‘trolling’ may differ dramatically.

Horse_ebooks is spam content (or, spam detection evasion content) that that has turned into a viral meme. Trolls sometimes become accepted members of a web community, understood to be entertaining and serving as rites of passage to n00bs. So these roles are not necessarily fixed.

With so much data about such roles available for analysis, research into these questions could teach us a lot more about human communication and conflict.