The current extent of ill mental health is estimated to cost the UK economy £105 billion per year in healthcare expenditure and lost revenue. Addressing mental health is therefore a clearly articulated priority for government. The broad use of ICT services, social media and smartphone applications has an increasingly important role to play in the delivery of clinical mental health services and in supporting societal mental health and wellbeing more generally. Indeed, for large sections of the population, and younger people in particular, the use of Social Computing technologies such as Facebook, Twitter and YouTube is already informally entwined with every facet of everyday life including health and wellbeing. The expectation by the healthcare community, and by commercial software developers, therefore is that digital mobile and social technology can provide compelling, scalable and convenient access to information, social and peer support, as well as therapy and shared self-monitoring tools and services. However, there are a numerous difficult challenges associated with the design, deployment, use and evaluation of such technology in mental health settings which must be solved using multidisciplinary, rigorous and scientific methods. The research field of Social Computing broadly focusses on the user-centred design, implementation, use, and evaluation of technologies that consider social context in an increasingly digitally-connected society. The UK's Social Computing research community therefore has a wealth of experience and expertise that is relevant to, but not typically directed at, mental health services and systems. This network will address issues of support, coordination and collaboration in this context and bring together two communities: (i) engineering and physical sciences (EPS) researchers under the broad, and inclusive, banner of Social Computing covering sub-fields of Human Computer Interaction (HCI), ubiquitous and mobile computing, and web science (ii) clinical scientists, healthcare professionals, commercial partners, charities, user groups and patients who are concerned with mental health and wellbeing. The network will work closely with the NIHR MindTech Healthcare Technology Co-operative (HTC) centre to engage in a range of coordinated scientific, technological, management and clinical activities to realise its overarching aim of pump-priming future UK capacity to deliver internationally-leading research at the boundaries between social computing and mental healthcare.

The current extent of ill mental health is estimated to cost the UK economy £105 billion per year in healthcare expenditure and lost revenue. Addressing mental health is therefore a clearly articulated priority for government. The broad use of ICT services, social media and smartphone applications has an increasingly important role to play in the delivery of clinical mental health services and in supporting societal mental health and wellbeing more generally. Indeed, for large sections of the population, and younger people in particular, the use of Social Computing technologies such as Facebook, Twitter and YouTube is already informally entwined with every facet of everyday life including health and wellbeing. The expectation by the healthcare community, and by commercial software developers, therefore is that digital mobile and social technology can provide compelling, scalable and convenient access to information, social and peer support, as well as therapy and shared self-monitoring tools and services. However, there are a numerous difficult challenges associated with the design, deployment, use and evaluation of such technology in mental health settings which must be solved using multidisciplinary, rigorous and scientific methods. The research field of Social Computing broadly focusses on the user-centred design, implementation, use, and evaluation of technologies that consider social context in an increasingly digitally-connected society. The UK's Social Computing research community therefore has a wealth of experience and expertise that is relevant to, but not typically directed at, mental health services and systems. This network will address issues of support, coordination and collaboration in this context and bring together two communities: (i) engineering and physical sciences (EPS) researchers under the broad, and inclusive, banner of Social Computing covering sub-fields of Human Computer Interaction (HCI), ubiquitous and mobile computing, and web science (ii) clinical scientists, healthcare professionals, commercial partners, charities, user groups and patients who are concerned with mental health and wellbeing. The network will work closely with the NIHR MindTech Healthcare Technology Co-operative (HTC) centre to engage in a range of coordinated scientific, technological, management and clinical activities to realise its overarching aim of pump-priming future UK capacity to deliver internationally-leading research at the boundaries between social computing and mental healthcare.

SOCIAM - Social Machines - will research into pioneering methods of supporting purposeful human interaction on the World Wide Web, of the kind exemplified by phenomena such as Wikipedia and Galaxy Zoo. These collaborations are empowering, as communities identify and solve their own problems, harnessing their commitment, local knowledge and embedded skills, without having to rely on remote experts or governments. Such interaction is characterised by a new kind of emergent, collective problem solving, in which we see (i) problems solved by very large scale human participation via the Web, (ii) access to, or the ability to generate, large amounts of relevant data using open data standards, (iii) confidence in the quality of the data and (iv) intuitive interfaces. "Machines" used to be programmed by programmers and used by users. The Web, and the massive participation in it, has dissolved this boundary: we now see configurations of people interacting with content and each other, typified by social web sites. Rather than dividing between the human and machine parts of the collaboration (as computer science has traditionally done), we should draw a line around them and treat each such assembly as a machine in its own right comprising digital and human components - a Social Machine. This crucial transition in thinking acknowledges the reality of today's sociotechnical systems. This view is of an ecosystem not of humans and computers but of co-evolving Social Machines. The ambition of SOCIAM is to enable us to build social machines that solve the routine tasks of daily life as well as the emergencies. Its aim is to develop the theory and practice so that we can create the next generation of decentralised, data intensive, social machines. Understanding the attributes of the current generation of successful social machines will help us build the next. The research undertakes four necessary tasks. First, we need to discover how social computing can emerge given that society has to undertake much of the burden of identifying problems, designing solutions and dealing with the complexity of the problem solving. Online scaleable algorithms need to be put to the service of the users. This leads us to the second task, providing seamless access to a Web of Data including user generated data. Third, we need to understand how to make social machines accountable and to build the trust essential to their operation. Fourth, we need to design the interactions between all elements of social machines: between machine and human, between humans mediated by machines, and between machines, humans and the data they use and generate. SOCIAM's work will be empirically grounded by a Social Machines Observatory to track, monitor and classify existing social machines and new ones as they evolve, and act as an early warning facility for disruptive new social machines. These lines of interlinked research will initially be tested and evaluated in the context of real-world applications in health, transport, policing and the drive towards open data cities (where all public data across an urban area is linked together) in collaboration with SOCIAM's partners. Putting research ideas into the field to encounter unvarnished reality provides a check as to their utility and durability. For example the Open City application will seek to harness citywide participation in shared problems (e.g. with health, transport and policing) exploiting common open data resources. SOCIAM will undertake a breadth of integrated research, engaging with real application contexts, including the use of our observatory for longitudinal studies, to provide cutting edge theory and practice for social computation and social machines. It will support fundamental research; the creation of a multidisciplinary team; collaboration with industry and government in realization of the research; promote growth and innovation - most importantly - impact in changing the direction of ICT.

SOCIAM - Social Machines - will research into pioneering methods of supporting purposeful human interaction on the World Wide Web, of the kind exemplified by phenomena such as Wikipedia and Galaxy Zoo. These collaborations are empowering, as communities identify and solve their own problems, harnessing their commitment, local knowledge and embedded skills, without having to rely on remote experts or governments. Such interaction is characterised by a new kind of emergent, collective problem solving, in which we see (i) problems solved by very large scale human participation via the Web, (ii) access to, or the ability to generate, large amounts of relevant data using open data standards, (iii) confidence in the quality of the data and (iv) intuitive interfaces. "Machines" used to be programmed by programmers and used by users. The Web, and the massive participation in it, has dissolved this boundary: we now see configurations of people interacting with content and each other, typified by social web sites. Rather than dividing between the human and machine parts of the collaboration (as computer science has traditionally done), we should draw a line around them and treat each such assembly as a machine in its own right comprising digital and human components - a Social Machine. This crucial transition in thinking acknowledges the reality of today's sociotechnical systems. This view is of an ecosystem not of humans and computers but of co-evolving Social Machines. The ambition of SOCIAM is to enable us to build social machines that solve the routine tasks of daily life as well as the emergencies. Its aim is to develop the theory and practice so that we can create the next generation of decentralised, data intensive, social machines. Understanding the attributes of the current generation of successful social machines will help us build the next. The research undertakes four necessary tasks. First, we need to discover how social computing can emerge given that society has to undertake much of the burden of identifying problems, designing solutions and dealing with the complexity of the problem solving. Online scaleable algorithms need to be put to the service of the users. This leads us to the second task, providing seamless access to a Web of Data including user generated data. Third, we need to understand how to make social machines accountable and to build the trust essential to their operation. Fourth, we need to design the interactions between all elements of social machines: between machine and human, between humans mediated by machines, and between machines, humans and the data they use and generate. SOCIAM's work will be empirically grounded by a Social Machines Observatory to track, monitor and classify existing social machines and new ones as they evolve, and act as an early warning facility for disruptive new social machines. These lines of interlinked research will initially be tested and evaluated in the context of real-world applications in health, transport, policing and the drive towards open data cities (where all public data across an urban area is linked together) in collaboration with SOCIAM's partners. Putting research ideas into the field to encounter unvarnished reality provides a check as to their utility and durability. For example the Open City application will seek to harness citywide participation in shared problems (e.g. with health, transport and policing) exploiting common open data resources. SOCIAM will undertake a breadth of integrated research, engaging with real application contexts, including the use of our observatory for longitudinal studies, to provide cutting edge theory and practice for social computation and social machines. It will support fundamental research; the creation of a multidisciplinary team; collaboration with industry and government in realization of the research; promote growth and innovation - most importantly - impact in changing the direction of ICT.