Towards a classification framework for social machines copy

May 13, 20130 likes578 views

This document proposes a framework for classifying social machines. It defines social machines and related concepts. An initial set of constructs for describing social machines was developed through elicitation grids. The constructs cluster into four groups: popularity, tasks/purpose, participants/roles, and motivation/incentives. The framework is intended to facilitate understanding and comparison of social machines. Further refinement of constructs and community evaluation are needed to improve the framework.

Towards a classification
framework for social machines
Submission at the SOCM2013 workshop @ WWW2013
Elena Simperl, Max Van Kleek
13 March 2013

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
�C Identify and define the constructs to describe, study and compare
social machines
�C 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

Social machines and related areas
? Social machines
�C Interaction among
algorithmic and social
components
�C Different notion of
computation (cf Turing) w.r.t.
problem specification,
performance, quality of
outputs, termination
�C Incentives and motivation,
network effects
? Related areas
�C Computer science: CSCW,
social computing, human
computation
�C Organizational
management/social sciences:
wisdom of the crowds,
collective intelligence, open
innovation, crowdsourcing
3

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

Challenges and research questions
? What do specific instances of a social machine have in
common, and how do they differ dynamically?
? How do certain design decisions taken at the level of the
infrastructure, frameworks and service propagate into
narrower-focused systems?
? How do such decisions affect a broader ecosystem of social
machines, each with their own, though overlapping,
purposes and communities?
5

Framework overview
? 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,
four clusters
�C Popularity
�C Tasks and purpose
�C Participants and roles
�C Motivation and incentives
6

Constructs: purpose of the system and contributions
? Purpose of the system, types of contributions, degree to
which these change
7

Constructs: people, roles, motivation
? Types of audience, autonomy and anonymity, roles and role
hierarchies
? Intrinsic vs. extrinsic motivation, rewards
8

Next steps: refine constructs
? Standard listings for types of contributions, actions, activities
? Relationship between roles, autonomy, and anonymity and motivators
? Motivation and incentives: participation in the definition of the overall purpose,
transparency of purpose
? Missing
�C Nature of the good produced
�C Existing social structures
�C Interaction between algorithmic and social components, workflows
�C Consolidation and aggregation of contributions, quality assurance
10

Next steps: community engagement and evaluation
? Community engagement: building a social machine to
define the SOCIAM classification framework
? Evaluation:
�C Task-independent using criteria from knowledge
engineering (completeness, correctness, readability,
redundancy etc)
�C Task-dependent: Can the framework be used to describe
existing social machines?
11

This document proposes a framework for classifying social machines. It defines social machines as systems involving both algorithmic and social components that interact and evolve over time. The objectives are to identify constructs for describing and comparing social machines. A methodology elicited constructs from examples of social machines. The resulting classification framework clusters constructs around general description, purpose/tasks, participants/roles, motivation/incentives, and technology. Next steps involve evaluating the framework's completeness and usefulness for describing existing social machines. The goal is a shared understanding to advance research and development of these complex, evolving systems.

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Towards a classification framework for social machines copy

1. Towards a classification framework for social machines Submission at the SOCM2013 workshop @ WWW2013 Elena Simperl, Max Van Kleek 13 March 2013

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 �C Identify and define the constructs to describe, study and compare social machines �C 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. Social machines and related areas ? Social machines �C Interaction among algorithmic and social components �C Different notion of computation (cf Turing) w.r.t. problem specification, performance, quality of outputs, termination �C Incentives and motivation, network effects ? Related areas �C Computer science: CSCW, social computing, human computation �C Organizational management/social sciences: wisdom of the crowds, collective intelligence, open innovation, crowdsourcing 3

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. Challenges and research questions ? What do specific instances of a social machine have in common, and how do they differ dynamically? ? How do certain design decisions taken at the level of the infrastructure, frameworks and service propagate into narrower-focused systems? ? How do such decisions affect a broader ecosystem of social machines, each with their own, though overlapping, purposes and communities? 5

6. Framework overview ? 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, four clusters �C Popularity �C Tasks and purpose �C Participants and roles �C Motivation and incentives 6

7. Constructs: purpose of the system and contributions ? Purpose of the system, types of contributions, degree to which these change 7

8. Constructs: people, roles, motivation ? Types of audience, autonomy and anonymity, roles and role hierarchies ? Intrinsic vs. extrinsic motivation, rewards 8

9. Using the constructs 9

10. Next steps: refine constructs ? Standard listings for types of contributions, actions, activities ? Relationship between roles, autonomy, and anonymity and motivators ? Motivation and incentives: participation in the definition of the overall purpose, transparency of purpose ? Missing �C Nature of the good produced �C Existing social structures �C Interaction between algorithmic and social components, workflows �C Consolidation and aggregation of contributions, quality assurance 10

11. Next steps: community engagement and evaluation ? Community engagement: building a social machine to define the SOCIAM classification framework ? Evaluation: �C Task-independent using criteria from knowledge engineering (completeness, correctness, readability, redundancy etc) �C Task-dependent: Can the framework be used to describe existing social machines? 11

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