We study Humanitarian Informatics as the interdisciplinary science of design, analysis, and evaluation of information systems concerned with welfare of human society that aims to create new knowledge in information representation and processing, for the fundamental challenge of information overload in organizational decision support.
Our lab researches the following basic human behavior modeling problems to address the information overload challenge (check projects) by mining online social and Web as well as offline data sources with text mining and machine learning methods guided by domain semantics and socio-psychological theories. We strive to conduct foundational research and evaluate that with real-world application challenges in the crisis management cycle of natural (e.g., hurricanes), societal (e.g., migration, gender stereotyping) and human (e.g., terrorism, cyber warfare) crises.
Cooperation between Citizens and Organizations in Smart Communities
(Cooperative Information System)
Social media, Web and Internet of Things have revolutionized information generation, transmission, and consumption, especially unstructured data, which has presented an information overload challenge for answering a variety of questions for organizational sensemaking. This project investigates the basic questions of organizational decision support and cooperation using novel behavioral data analytics methods, such as what is actionable in data streams to help articulated organizational work, how to extract information for such articulation tasks, whom to trust and engage in the online community for information, etc.
Collaborators: Fairfax County Fire & Rescue, Virginia; California Governor's Office of Emergency Services
Project Supported by: NSF award #1657379 (CRII: CHS: Mining Intentions on Social Media to Enhance Situational Awareness of Crisis Response Organizations), Research Council of Norway award #261685 (INTPART: Transnational Partnership for Excellent Research and Education in Big Data and Emergency Management)
User attitudes & Engagement
(Semantic Machine Learning)
Do you know that gender-based violence is a public health crisis and what are its impact on healthcare system? Do you wonder why people migrate from certain regions and what are the implications of migration? The objective of this project is to reduce information overload for responding (non-)governmental organizations in gleaning insights about public awareness and attitudes towards societal crises prevalent in the modern age (e.g., views on violence against women and narratives about refugee migration), in order to inform the organizations in their evaluation of awareness campaigns, intervention support, and policy design practices.
Collaborators: Internal Displacement Monitoring Centre, Geneva; The Port Association by CERN Researchers, Geneva; Civic Nation, Washington D.C.
Project Partially Supported By: GMU Startup Funds and NSF award #1707837 (EAGER: Social Media Participation as Indicator of Actors, Awareness, Attitudes, and Activities Related to STEM Education).
Comprehension & Cognitive Load
Can an organization mitigate the crisis of losing intellectual property in response to human-created crisis of cyber attacks? This project investigates how we can create information overload for hackers to prevent them from stealing information by better understanding of information comprehension and cognitive load. Such an approach can improve cyber defense tactices for human crisis management as well as create opportunities to design tools and techniques for managing information overload in any tech-assisted environment.
Project Supported By: Office of Naval Research award #N00014-16-1-2896 (Believable Fake Documents)
- Prof. Hemant Purohit
- Prakruthi Karuna (PhD IT - IST Concentration, GMU)
- Rahul Pandey (PhD IT - IST Concentration, GMU)
- Cooper Jessup (PhD IT - IST Concentration, GMU)
- Bahman Pedrood (PhD research assistant, GMU)
- Yogen Chaudhari (MS research assistant, GMU)
- Sharan Banola (MS research assistant, GMU)