Cognitive Machines
Designing media technologies for social engagement and change.
The goal of the Cognitive Machines group is to create systems that engage in fluid, situated, meaningful communication with human partners. We seek to understand and model the processes by which words are grounded in the physical world as a result of embodied perception, action, and learning. These models are applied to create situated human-machine interfaces. We also use our computational models as a source of predictions and possible accounts for a number of cognitive phenomena including aspects of children's language acquisition, concept formation, and attention.

Research Projects

  • Media Ecosystem Analysis: Lessons from the Boston Marathon Bombings

    Soroush Vosoughi and Deb Roy

    In this project we examine the social media and traditional media's response to the Boston Marathon bombings from the moment of the explosion to two weeks after the events, including the search, hunt, and capture of the suspects. We use big data analytics, natural language processing, and complex system and network analysis techniques. We focus specifically on information flow, engagement and attention of the audience, emergence of broadcasters, source and spread of rumors, and interplay of various media. We hope to develop a better understanding of the nature of information generation and flow from broadcasters and audiences across different media. Using this event as a case study, we can find out what went wrong or right, and come up with recommendations for different actors (news sources, social media participants, police departments) to better facilitate information flow and minimize misunderstanding and the spread of false information.

  • Rumors in Social Networks: Detection, Verification and Intervention

    Soroush Vosoughi and Deb Roy

    Motivated by the role that rumors played in the aftermath of the Boston Marathon bombings, we study the emergence, spread, and veracity of rumors in large, complex, and highly connected message passing systems such as social media platforms, with a particular focus on rumors surrounding emergencies. We are using the Boston Marathon bombings as a case study to develop computational models of rumors that can be used to predict the veracity, spread, and impact of rumors surrounding particular events. The end goal is to create an online rumor verification algorithm that can analyze rumors in real-time as events unfold. We hope our tool can be used by citizens, journalists, and emergency services to minimize the spread and impact of false information in social media during emergencies.