A Taxonomic Framework for Social Machines
A Taxonomic Framework for Social Machines
  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.
  social machines, social computing, Web science, collective intelligence, social Web, taxonomy, socio-technical systems, human computation, crowdsourcing
  
  51-85
  
  
    
      Smart, Paul R
      
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      Simperl, Elena
      
        40261ae4-c58c-48e4-b78b-5187b10e4f67
      
     
  
    
      Shadbolt, Nigel
      
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      1 October 2014
    
    
  
  
    
      Smart, Paul R
      
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      Simperl, Elena
      
        40261ae4-c58c-48e4-b78b-5187b10e4f67
      
     
  
    
      Shadbolt, Nigel
      
        5c5acdf4-ad42-49b6-81fe-e9db58c2caf7
      
     
  
    
  
    
  
    
  
    
  
    
  
       
    
 
  
    
      
  
  
  
  
    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, .
  
  
  
  (doi:10.1007/978-3-319-08681-1_3).
  
   
  
    
      Record type:
      Book Section
      
      
      
    
   
    
    
      
        
          Abstract
          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.
         
      
      
        
          
            
  
    Text
 SOCIAM Classificationv2.pdf
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      e-pub ahead of print date: 23 August 2014
 
    
      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
      
    
  
    
  
  
  
    
  
  
        Identifiers
        Local EPrints ID: 362359
        URI: http://eprints.soton.ac.uk/id/eprint/362359
        
          
        
        
        
        
          PURE UUID: 0d408c72-8728-49d4-9f5e-770bec4edd68
        
  
    
        
          
            
              
            
          
        
    
        
          
            
              
            
          
        
    
        
          
            
          
        
    
        
          
            
          
        
    
        
          
            
          
        
    
        
          
            
          
        
    
        
          
            
          
        
    
        
          
            
          
        
    
  
  Catalogue record
  Date deposited: 20 Feb 2014 16:47
  Last modified: 22 Aug 2025 01:50
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      Contributors
      
          
          Author:
          
            
              
              
                Paul R Smart
              
              
                
              
            
            
          
         
      
        
      
          
          Author:
          
            
              
              
                Nigel Shadbolt
              
              
            
            
          
        
      
          
          Editor:
          
            
              
              
                Daniele Miorandi
              
              
            
            
          
        
      
          
          Editor:
          
            
              
              
                Vincenzo Maltese
              
              
            
            
          
        
      
          
          Editor:
          
            
              
              
                Michael Rovatsos
              
              
            
            
          
        
      
          
          Editor:
          
            
              
              
                Anton Nijholt
              
              
            
            
          
        
      
          
          Editor:
          
            
              
              
                James Stewart
              
              
            
            
          
        
      
      
      
    
  
   
  
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