Crowdsourced Ethics With Personalized Story Matching

Henry Lieberman, Karthik Dinakar, Birago Jones


Cyberbullying is a widespread and growing social problem, threatening the viability of social networks for youth. We believe that one of the best ways to combat this problem is to use these incidents as “teaching moments”, encouraging teens to reflect on their behavior and choices. Sites that offer community discussions around the ethical aspects of social situations can help teens feel less alone in their plight, and provide useful advice and emotional support. But the success of these “crowdsourced ethics” sites depends critically on the user feeling like discussions are relevant to their own personal experience. We have augmented the crowdsourced ethics site “Over The Line”, offered by MTV Networks, with a personalized story matcher that classifies stories according to dynamically discovered high-level themes like “sending nude pictures online” or “feeling pressure in relationships”. The matcher uses a mixed-initiative LDA machine learning technique [2], and a commonsense knowledge base specialized to the bullying problem. The site is currently public, and attracts an audience of thousands of users daily.

Related Content