Methodologically, our principal sub-areas are: (i) computational social science: studying human behavior at scale, (ii) social analytics: applying machine learning to social data to build models for various applications, and (iii) hybrid collaborative intelligence: supporting the collaboration between humans and machines for information processing tasks.
Thematically, our group is organized by application areas: Health, Urban Computing, Crisis Computing and News. The researchers in each focus area work with local stakeholders to generate science and systems that are locally relevant to the region, while producing global impact. Our efforts in these four areas are elaborated on below.
Public health informatics for healthy living: We develop technologies to promote healthy living of individuals, communities and populations. In our work, we focus on lifestyle as many countries, including Qatar, struggle with a continuous increase in lifestyle-related diseases such as obesity. We work closely with local domain experts to apply our extensive experience in social media research, mobile technologies and wearables to improve health in the region and worldwide. Part of our work focuses on analyzing and visualizing social media data to better understand public health concerns, especially lifestyle-related issues. Furthermore, we combine social media, wearable and mobile technologies to create patient-centric quantified-self systems to support decision making of healthcare professionals and patients.
Using big data to understand urban dynamics in fast-growing cities: Fast-growing cities like Doha face several challenges such as providing good transportation networks, sustainable energy sources, acceptable commute times, and so on. Complementary to physical data sensing and acquisition, data from social media describing all types of events unfolding in the city can be exploited to address these challenges and better “sense” the city for improving current urban services, for decision-making and future planning. At QCRI we are working on a platform for integrating data from disparate physical and social sensors and we are currently developing novel analytical approaches to mine such data and design various smart city apps for residents. The overall goal is to help citizens in their everyday lives in urban spaces, and also help transportation experts and policy specialists to take a real time, data-driven approach towards urban planning and real-time traffic planning in the city.
Extracting timely and credible information from social media for crisis response: We conduct applied and core computer science research and build innovative technologies that can be used by policymakers, NGOs, affected communities and scholars to improve the effectiveness of humanitarian strategies such as preparedness, mitigation, and response during humanitarian crises and emergencies. We apply natural language processing, machine learning, and computer vision techniques to crisis information communicated via social media to gain situational awareness for humanitarian response. Our research and development efforts focus on consuming social media content available in multiple forms, both textual and visual, on Twitter and Facebook, and is coordinated in collaboration with several regional and global partners including UN OCHA, UNICEF, and Suffolk County Fire and Emergency Department in New York.
News and social media analytics: We conduct research to understand, predict, and improve the dissemination of news in all of its forms by employing all types of online data. Our research objectives are to provide regional and other policy makers insights concerning the impact of online news, develop methods leveraging social media and other online data to inform journalists and content providers allowing them to understand and enhance exposure in real time, and build real-time systems to facilitate the analysis of online news and enhance its impact.
For more details about our projects, demos, and publications, please visit our group page at sc.qcri.org.