by Rob Morris (Massachusetts Institute of Technology)
Can we gauge the affective state of the crowd? Is the crowd happy? Stressed out? Bored to tears? For many crowdsourcing applications, these questions are crucial. So, how do we answer them? Well, we could always just ask the crowd outright, and administer questionnaires. Or, we could use implicit, behavioral measures, such as those described by Michael Toomim. But we might also benefit from tools that measure affective features directly, in real-time.
Thanks to advances in affective computing, such tools are now at our disposal. In many cases, all we really need is a webcam. Indeed, with just an ordinary webcam, we can now monitor a vast array of affective features, such as posture, facial expression, and heart-rate.
In the Affective Computing Group at MIT, we are applying these techniques to a variety of real-world crowdsourcing applications. For instance, Dan McDuff, a PhD student in our group, is currently tracking facial expressions from thousands of people online, while they watch superbowl advertisements. As part of an art installation, Javier Hernandez-Rivera and Ehsan Hoque are tracking smiles at different locations throughout the MIT campus. With their system, we can start to answer an age-old MIT question – who’s happier: computer science students or media arts students?
Both of these examples use crowdsourcing techniques to acquire massive amounts of naturalistic affective data. But, we could just as easily turn these examples on their head, and use the same tools to reflect back on our crowdsourcing designs and methodologies – how do our designs affect the emotions of the crowd?
As crowdsourcing researchers, we must remember that emotions are a fundamental part of what makes us human. And, since crowdsourcing is essentially a humanistic field, it behooves us to at least consider the affective states of the crowd. Doing so will help us design better technologies, and it will open doors to many new research areas (several of which I describe in my position paper). Emotions, and indeed all affective phenomena, can bring a lot to bear to our field.
Rob Morris is a 2nd-year PhD student in the Affective Computing Group at MIT. He is currently interested in how crowdsourcing technologies might foster new forms of nearly real-time, emotion regulatory support.