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.

1. Towards a classification
framework for social machines
Submission at SOCM2013@WWW2013
Elena Simperl
26 April 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
– 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. Theory and practice
of social machines
May 13, 2013
14

15. Constructs: purpose of the system and contributions
• Purpose of the system, types of contributions, degree to
which these change
15

16. Constructs: people, roles, motivation
• Types of audience, autonomy and anonymity, roles and role
hierarchies
• Intrinsic vs. extrinsic motivation, rewards
16