Design for Collective Action
From Twitter hashtags such as #metoo to protests by Mechanical Turk workers in the public sphere, collectives come together online to make progress on shared issues. My research introduces social computing systems that directly center trust and familiarity to more effectively support collective action. I will demonstrate this concept through two projects. The first, Hive, explores how social systems can help build strong networks by organizing a collective into small teams, then intermixing viewpoints by gradually rotating team membership. I deployed this project with Mozilla to reimagine accessible web browsing with disability advocates online. My second project, Dynamo, shows how structured human labor can help move efforts forward when they stall. I undertook this project in collaboration with worker rights advocates on Amazon Mechanical Turk. Through this work I envision alternate roles for social computing ecosystems in society that directly support efforts for social change.
Niloufar Salehi is a Ph.D. candidate in computer science at Stanford University where she studies human-computer interaction. Her research interests are in social computing, technologically mediated collective action, digital labor, and computer supported cooperative work. Her work has been published and received awards in premier venues in human-computer interaction including CHI and CSCW. She has been awarded a Stanford Graduate Fellowship and a Stanford School of Engineering Fellowship. Through building computational social systems in collaboration with existing communities, controlled experiments, and ethnographic fieldwork, her research contributes the design of alternative social configurations online.