The Theory and Practice of Social Machines pp 103-147 | Cite as
Practice
Abstract
This chapter examines how social machines work in practice, and how researchers can understand them and intervene them when appropriate. It begins with a discussion of how to gather the evidence about social machines, and introduces the idea of a distributed Web Observatory, looking at the specific example of the Southampton University Web Observatory (SUWO). Next the chapter looks at how to model crowds, and how crowds behave, considering the motivations, including social and financial incentives, for participating in social machines and more generally in crowdsourcing exercises, and how participants can be encouraged to engage, especially if they are deemed likely to disengage. The next section takes a deeper dive into the citizen science platform Zooniverse, and considers how the architecture is designed to promote flourishing social groups and productive sociality, creating value for both participants and scientists; some principles for citizen science platform design are set out. Finally, more examples of social machines in action are described, including social machines in mathematics, in politics and in music, before the chapter finishes with a further look at Wikipedia in the context of theories about the affordances of institutions for supporting creativity.
Keywords
Brexit Citizen science Clinton, Hillary Common-pool resources Computational social creativity CrowdFlower Crowdsourcing Disengagement Duolingo Eyewire Financial incentives Galaxy Zoo Incentives Mathematical social machines Mathematics Stack Exchange MathOverflow Motivation Music Information Retrieval (MIR) Musical social machines Obama, Barack Ostrom, Elinor Panoptes (Zooniverse) Political social machines Project builder (Zooniverse) Romney, Mitt Social flow Social incentives Southampton University Web Observatory (SUWO) Talk pages (Zooniverse) Trump, Donald Twitter Web Observatory Wikipedia WikiProjects ZooniverseReferences
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