Manifesto of computational social science

The increasing integration of technology into our lives has created unprecedented volumes of data on society’s everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computational Social Science. Against a background of financial crises, riots and international epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, technology and society that the success of this endeavour is likely to bring about. 1 Objectives and opportunities In a world of demographic explosion, global crises, ethnic and religious disturbances and increasing crime the understanding of the structure and function of society, as well as the nature of its changes, is crucial for governance and for the well being of people. Humanity is currently facing grand challenges. Setting aside environmental issues and the depletion of natural resources, we have to cope with formidable social and political problems: a e-mail: [email protected] 326 The European Physical Journal Special Topics – Change of the population structure (change of birth rate, migration); – Financial and economic instability (trust, consumption and investments; sovereign debt, taxation, and inflation/deflation; sustainability of social welfare systems, and so on); – Social, economic and political divide (among people of different gender, age, education, income, religion, culture, language, preferences); – Threats against health (due to the spreading of epidemics, but also to unhealthy diets and habits); – Unbalance of power in a multi-polar world; – Organized crime, including cyber-crime, social unrest and war; – Uncertainty in institutional design and dynamics (regarding regulations, authority, corruption, balance between global and local, central and decentralized systems); – Unethical usage of communication and information systems (cyber risks, violation of privacy, misuse of sensitive data, spam). In the last couple of years, social scientists have started to organize and classify the number, variety, and severity of criticalities, if not pathologies and failures, recurring in complex social systems [1,2]. These are amongst the most severe social problems, difficult to predict and treat, and raising serious social alarm. Furthermore, human society has never before changed as fast as it is changing today. Technological development has opened entirely new channels of communication, induced new behavioural patterns, substantially influenced organization principles, and its products are becoming history-forming factors. We human beings have preserved our basic, genetically determined biological properties over tens of thousands of years but our social behaviour seems to be altered with an unprecedented speed, continuously challenging our adaptivity. Part of the difficulty for us to respond to the challenges mentioned above is inherent to fundamental features of social complexity. Complex social systems are characterised by multiple ontological levels with multidirectional connections, proceeding not only from the micro to the macroscopic levels but also back from the macro to the micro-levels [3]. Furthermore, complex social systems present a far-reaching and accelerated diffusion of phenomena, behaviours and cultural traits. Accelerated contagion leads on one hand to new systems’ properties emerging at the aggregate level – for example new public opinions and political movements, new global and local identities, collective preferences, attitudes, even moods, etc. – and on the other to major critical event in the social economic and/or political spheres, such as global financial crises and the collapse of regimes. Finally, complex social systems do often show interdependences and interferences among their properties and processes of transformation. The interplay between cultural and biological evolution shows unexpected intricacies, far from the parallel predicted by the Dual Inheritance Theory [4], as shown by the Demographic Transition (DT) model [5]. Based on an interpretation of demographic history developed in 1929 by the American demographer Warren Thompson, the DT model points to a growing gap between economic and demographic growth: all over the world, the higher the average income of the population the lower its birth rate. These problems depend on the same circumstances that might help us find solutions: a high degree of poorly understood and poorly investigated technology-driven innovation. ICT applications seem to act both in favour and against our capacity to answer the grand challenges before us. The widespread access to the Internet is seriously and often positively impacting the frequency, range and style of human communication and interaction, leading to heterogeneous interconnected networks. Electronic communications seem to have played a fundamental role in the diffusion and organization of the protest movements arising in Northern Africa, and leading to regime change. At the same time, the view that social networks connect people is Participatory Science and Computing for Our Complex World 327 oversimplified, and the question remains open as to what types of connections are established among them, whether, for example, pro or antisocial, and – since resources like time are limited – to the expense of what and of whom. The alternative offered by Internet to the hierarchical organization of cultural production and specialised professional advice pushes up symmetrical, horizontal interactions. At the same time, the Open Source community challenges the foundation of intellectual property as well as the institution of truth certification. Are these effects only signs of providential progress? What about the nature and functioning of economic, cultural and political institutions? What about the credibility of the information spread and its effective truth-value? That much for the negative side of the coin. But there is also a positive side. Information and communication technologies can greatly enhance the possibility to uncover the laws of the society. First, ICT produces a flood of data. These data represent traces of almost all kinds of activities of individuals enabling an entirely new scientific approach for social analysis. Second, the development of computer capacities makes it possible to handle the data deluge and to invent models that reflect the diversity and complexity of the society. The analysis of huge data sets as obtained, say, from mobile phone calls, social networks, or commercial activities provides insight into phenomena and processes at the societal level. Investigating peoples’ electronic footprints did already contribute to understand the relationship between the structure of the society and the intensity of relationships [6] and the way pandemic diseases spread [7], as well as to identify the main laws of human communication behaviour [8]. The traditional tools of social sciences would at most scratch the surface of these issues, whereas new tools can shed light onto social behaviour from totally different angles. Possibilities ranging from supercomputers to distributed computing make the execution of large-scale, heterogeneous multi-agent programs possible, programs which prove particularly apt to model the complexity of social and behavioural systems. The new ICT-enabled study of society has been named computational social science [9]. This is a truly interdisciplinary approach, where social and behavioural scientists, cognitive scientists, agent theorists, computer scientists, mathematicians and physicists cooperate side-by-side to come up with innovative and theory-grounded models of the target phenomena. Computational social scientists strongly believe that a new era has started in the understanding of the structure and function of our society at different levels [9]. On the one hand, computational social science is aimed to favour and take advantage of massive ICT data. On the other, it is a model-based science yielding both predictive and explanatory models. Hence, it is intended to profit from the modelling instruments made available by ICT for producing generative models of large-scale multi-agent systems. Both objectives must be achieved to turn social science into applicable tools that can inform decision makers about issues of major concern. In this paper, we will work towards the drafting of a Manifesto for the new Computational Social Science. The paper will unfold as follows: in the next section, the state of the art of the field will be discussed. In the third section, its main characteristics will be examined. In the fourth section, the main challenges the new field is facing will be addressed. Finally, in the fifth section, we will turn our attention to compare and discuss the types of models that are compatible or necessary for a computational social scientific program as outlined in the previous part of the paper. Final considerations will conclude the paper, but not the process to constitute the new discipline, that for a Computational Social Science is an inherently dynamic scientific program. This paper is only part of the beginning of it. 328 The European Physical Journal Special Topics