A group of researchers has developed a machine learning model that can detect tweets relating to bullying, and even identify bullies, victims and witnesses. Next, it wants to add sentiment analysis to determine individuals’ emotional states. But if they see trouble, how do they intervene?
We already know how powerful techniques such as machine learning and sentiment analyis can be when it comes to deciphering consumer behavior online, and now it seems they can identify bullies, as well. A group of University of Wisconsin researchers have developed a machine learning algorithm that’s identifying more than 15,000 tweets per day relating to bullying — complete with loads of associated sociological insights — which begs the question of how to act on that data. How do you govern a social web that can be simultaneously a communication platform, a research lab full of unknowing subjects and a boiling-over pot of criminal evidence?
