This open access handbook describes foundational issues, methodological approaches and examples on how to analyse and model data using Computational Social Science (CSS) for policy support. Up to now, CSS studies have mostly developed on a small, proof-of concept, scale that prevented from unleashing its potential to provide systematic impact to the policy cycle, as well as from improving the understanding of societal problems to the definition, assessment, evaluation, and monitoring of policies. The aim of this handbook is to fill this gap by exploring ways to analyse and model data for policy support, and to advocate the adoption of CSS solutions for policy by raising awareness of existing implementations of CSS in policy-relevant fields. To this end, the book explores applications of computational methods and approaches like big data, machine learning, statistical learning, sentiment analysis, text mining, systems modelling, and network analysis to different problems in the social sciences. The book is structured into three Parts: the first chapters on foundational issues open with an exposition and description of key policymaking areas where CSS can provide insights and information. In detail, the chapters cover public policy, governance, data justice and other ethical issues. Part two consists of chapters on methodological aspects dealing with issues such as the modelling of complexity, natural language processing, validity and lack of data, and innovation in official statistics. Finally, Part three describes the application of computational methods, challenges and opportunities in various social science areas, including economics, sociology, demography, migration, climate change, epidemiology, geography, and disaster management. The target audience of the book spans from the scientific community engaged in CSS research to policymakers interested in evidence-informed policy interventions, but also includes private companies holding data that can be used to study social sciences and are interested in achieving a policy impact.

The recent containment policies aimed at regulating immigration flows towards Europe have profoundly altered the dynamics of migration in Africa. The impact of these policies is apparent in the redefinitions of the routes, itineraries and actors of migration. But their effect can also be felt in migrant categories and identities and in the perceptions of migrants in the societies through which they transit or the communities which they have left behind. By placing the problem of border control at the very heart of the migration issue, the policies aimed at the restriction of migration flows have changed the meaning and significance of migration. More than ever before, both migrants and institutions in charge of border control construe migration mostly around the challenge of border-crossing. In the Global South, the transit situation in which would-be border jumpers are retained blurs the distinction between temporary migration and settlement. This contributes to change, in various ways, the relationship to strangers, from renewed forms of solidarities to the reactivation of latent xenophobic sentiment, whether around the Mediterranean or en route towards South Africa, the other migration hub on the continent. The editors of this volume have decided to work on the notion of "threshold" as an operative concept for addressing the multiple dimensions of the issue: the discursive and conceptual frameworks that constitute the backbone of threshold policies aiming to keep undesirables beyond borders; the constitution of stopping places, intermediate areas and relay towns, which all represent threshold spaces that challenge local urban equilibria; and the experience of liminality, in which individuals caught for a time between two states (as migrant on the road and as immigrant, the state to which they aspire), experience the typically ambiguous situations characteristic of 'threshold people' (Turner). While ambitioning to innovate theoretically and methodologically, the volume is above all

This open access handbook describes foundational issues, methodological approaches and examples on how to analyse and model data using Computational Social Science (CSS) for policy support. Up to now, CSS studies have mostly developed on a small, proof-of concept, scale that prevented from unleashing its potential to provide systematic impact to the policy cycle, as well as from improving the understanding of societal problems to the definition, assessment, evaluation, and monitoring of policies. The aim of this handbook is to fill this gap by exploring ways to analyse and model data for policy support, and to advocate the adoption of CSS solutions for policy by raising awareness of existing implementations of CSS in policy-relevant fields. To this end, the book explores applications of computational methods and approaches like big data, machine learning, statistical learning, sentiment analysis, text mining, systems modelling, and network analysis to different problems in the social sciences. The book is structured into three Parts: the first chapters on foundational issues open with an exposition and description of key policymaking areas where CSS can provide insights and information. In detail, the chapters cover public policy, governance, data justice and other ethical issues. Part two consists of chapters on methodological aspects dealing with issues such as the modelling of complexity, natural language processing, validity and lack of data, and innovation in official statistics. Finally, Part three describes the application of computational methods, challenges and opportunities in various social science areas, including economics, sociology, demography, migration, climate change, epidemiology, geography, and disaster management. The target audience of the book spans from the scientific community engaged in CSS research to policymakers interested in evidence-informed policy interventions, but also includes private companies holding data that can be used to study social sciences and are interested in achieving a policy impact.