Towards a classification framework for social machines
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Transcript of Towards a classification framework for social machines
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Towards a classification framework for social machines
Submission at SOCM2013@WWW2013
Elena Simperl 26 April 2013
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Motivation and objectives • Future ICT systems as sophisticated assemblies of data-intensive, complex automation and
deep community involvement
• Defining social machines and their characteristic properties as necessary step towards a principled understanding of the science and engineering of such systems
• Objectives of this work
– Identify and define the constructs to describe, study, and compare social machines
– Achieve a shared understanding of basic notions and terminology through involvement from the broader community
• Useful tool for both researchers in social and computer sciences and for developers and operators of existing and future social machines
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General considerations
• Machine: ‘(1) an assemblage of parts that transmit forces, motion, and energy one to another in a predetermined manner; (2) an instrument (as a lever) designed to transmit or modify the application of power, force, or motion’ [Merriam-Webster]
• In relation to living beings: ‘one that resembles a machine (as in being methodical, tireless, or consistently productive)’ [Merriam-Webster]
• Social machine
1. co-existence of and interaction among algorithmic and social components;
2. problem/task specification changes as the system evolves;
3. operation of the system is governed by a different set of rules;
4. different performance models and approaches to measure them;
3 [Courtesy of Dave de Roure]
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The polyarchical relationship of social machines
• Platforms/technologies vs social machines created for specific purposes. E.g., MediaWiki vs Wikipedia
• Broader vs narrower-scoped social machines. E.g., Twitter vs Obama’12
• Ecosystem of social machines. E.g., results from GalaxyZoo taken up in Wikipedia articles
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Social machines and related areas
• Computer science: CSCW, social computing, human computation
• Organizational management/social sciences: wisdom of the crowds, collective intelligence, open innovation, crowdsourcing
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Social machines and related areas (2)
• Who defines the task/purpose of the system
– The system designer vs community
• What kind of tasks do humans undertake
– Creative vs computationally expensive
• Who is supporting whom
– Humans supporting algorithmic processes or machines supporting human tasks
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Methodology
• Repertory grid elicitation to derive an initial set of elements (instances of social machines) and constructs (characteristics of social machines) 10 grids, 56 elements, 117 constructs
• Consolidation and clustering of constructs 31 constructs, five clusters
– General description
– Purpose and tasks
– Participants and roles
– Motivation and incentives
– Technology
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Purpose and forms of contribution
• Contributions towards public vs private good
• Implicit vs explicit contributions
• Degree to which contributors decide what they can work on
• Degree to which contributors can change the nature/purpose/development of the social machine
• How is the final result created/aggregation
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Participation and interaction
• Who can contribute and what: roles, requester/worker, game models, skills and learning curve
• Workflow management: task/resource assignment (scarcity, requester-contributions cardinality), parallelization, synchronization, aggregation
– Machine replacing/assisting humans vs humans replacing machines
• Dynamics of participation model
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Quality and performance
• Which contributions are validated
• Is there a ground truth and where does it come from: no one, community, dedicated group, machine owner
• How is quality assessment performed: manually, agreement/voting between participants, computed automatically
• Are criteria and quality control methods explicit/transparent
• Can contributors change the criteria or earn the right to perform evaluations
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Motivation and incentives • Altruism
• Reciprocity
• Community
• Reputation
• Autonomy
• Entertainment/Fun
• Intellectual challenge
• Learning
• Competition
• Payment/Rewards
• Depend on
– Nature of the good produced
– Goal
– Nature of the contributions
– Existing social structure
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Technology and engineering • Requirements specification and evolution
• Security, trust
• Decentralization
• Data ownership and access
• Profile building
• Social networks
• Analytics on top of social network and actual data
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[Courtesy of Dave Robertson]
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Next steps
• Consolidate and use the classification
• Evaluation
– Task-independent using criteria from knowledge engineering (completeness, correctness, readability, redundancy etc)
– Task-dependent: Can the framework be used to describe existing social machines?
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Theory and practice of social machines May 13, 2013
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Constructs: purpose of the system and contributions
• Purpose of the system, types of contributions, degree to which these change
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Constructs: people, roles, motivation
• Types of audience, autonomy and anonymity, roles and role hierarchies
• Intrinsic vs. extrinsic motivation, rewards
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