Towards a classification
framework for social machines
Submission at SOCM2013@WWW2013
Elena Simperl
26 April 2013
Motivation and objectives
• Future ICT systems as sophisticated assemblies of data-intensive, complex automation and
deep ...
General considerations
• Machine: ‘(1) an assemblage of
parts that transmit forces,
motion, and energy one to
another in a...
The polyarchical relationship of social machines
• Platforms/technologies vs social machines created for specific
purposes...
Social machines and related areas
• Computer science:
CSCW, social computing,
human computation
• Organizational
managemen...
Social machines and related areas (2)
• Who defines the task/purpose of the system
– The system designer vs community
• Wh...
Methodology
• Repertory grid elicitation to derive an initial set of elements
(instances of social machines) and construct...
Purpose and forms of contribution
• Contributions towards public vs private good
• Implicit vs explicit contributions
• De...
Participation and interaction
• Who can contribute and what: roles, requester/worker,
game models, skills and learning cur...
Quality and performance
• Which contributions are validated
• Is there a ground truth and where does it come from: no one,...
Motivation and incentives
• Altruism
• Reciprocity
• Community
• Reputation
• Autonomy
• Entertainment/Fun
• Intellectual ...
Technology and engineering
• Requirements specification and evolution
• Security, trust
• Decentralization
• Data ownershi...
Next steps
• Consolidate and use the classification
• Evaluation
– Task-independent using criteria from knowledge
engineer...
Theory and practice
of social machines
May 13, 2013
14
Constructs: purpose of the system and contributions
• Purpose of the system, types of contributions, degree to
which these...
Constructs: people, roles, motivation
• Types of audience, autonomy and anonymity, roles and role
hierarchies
• Intrinsic ...
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Towards a classification framework for social machines

  1. 1. Towards a classification framework for social machines Submission at SOCM2013@WWW2013 Elena Simperl 26 April 2013
  2. 2. 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 2
  3. 3. 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]
  4. 4. 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 4
  5. 5. 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 5
  6. 6. 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 6
  7. 7. 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 7
  8. 8. 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 8
  9. 9. 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 9
  10. 10. 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 10
  11. 11. 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 11
  12. 12. 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 12 [Courtesy of Dave Robertson]
  13. 13. 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? 13
  14. 14. Theory and practice of social machines May 13, 2013 14
  15. 15. Constructs: purpose of the system and contributions • Purpose of the system, types of contributions, degree to which these change 15
  16. 16. Constructs: people, roles, motivation • Types of audience, autonomy and anonymity, roles and role hierarchies • Intrinsic vs. extrinsic motivation, rewards 16
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