The University of Southampton
University of Southampton Institutional Repository

A Taxonomic Framework for Social Machines

Smart, Paul R, Simperl, Elena and Shadbolt, Nigel (2014) A Taxonomic Framework for Social Machines In, Miorandi, Daniele, Maltese, Vincenzo, Rovatsos, Michael, Nijholt, Anton and Stewart, James (eds.) Social Collective Intelligence: Combining the Powers of Humans and Machines to Build a Smarter Society. Berlin, Germany, Springer pp. 51-85. (doi:10.1007/978-3-319-08681-1_3).

Record type: Book Section


As the Web has developed into a global social platform there has been increasing interest in a particular class of systems known as 'social machines'. Social machines are typically presented as systems that combine some form of social participation with conventional forms of machine-based 'computation'. Beyond this rather general characterization, however, there is little consensus as to what the term 'social machine' actually means. Furthermore, little has been done to explore the core features of social machines and examine differences between them. This limits our understanding of the kinds of social machines that currently exist, and it also limits our ability to imagine the kinds of social machine that could emerge in the future. In this chapter, we introduce a taxonomy for the description and classification of social machines that could be used to frame future scholarly discourse and identify aspects of the social machine research effort that deserve further consideration. As part of this effort, we propose a definition of social machines that puts them in relation to the broader class of socio-technical systems, while distinguishing them from other kinds of technology-mediated social participation system; for example, human computation systems and collective intelligence systems. The taxonomic framework we present serves to extend our understanding of social machines. It includes a total of 33 dimensions and 106 associated characteristics. Together, these specify the space of all (theoretically possible) social machine types.

PDF SOCIAM Classificationv2.pdf - Other
Download (459kB)

More information

Published date: 1 October 2014
Keywords: social machines, social computing, Web science, collective intelligence, social Web, taxonomy, socio-technical systems, human computation, crowdsourcing
Organisations: Web & Internet Science


Local EPrints ID: 362359
PURE UUID: 0d408c72-8728-49d4-9f5e-770bec4edd68
ORCID for Paul R Smart: ORCID iD
ORCID for Elena Simperl: ORCID iD

Catalogue record

Date deposited: 20 Feb 2014 16:47
Last modified: 18 Jul 2017 02:53

Export record



Author: Paul R Smart ORCID iD
Author: Elena Simperl ORCID iD
Author: Nigel Shadbolt
Editor: Daniele Miorandi
Editor: Vincenzo Maltese
Editor: Michael Rovatsos
Editor: Anton Nijholt
Editor: James Stewart

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.