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Social Phenomena : From Data Analysis to Models / edited by Bruno Gonçalves, Nicola Perra

Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Computational Social Sciences | SpringerLink BücherPublisher: [Cham, u.a.] : Springer, 2015Description: Online-Ressource (XII, 260 p. 71 illus., 67 illus. in color, online resource)ISBN:
  • 9783319140117
Subject(s): Additional physical formats: 9783319140100 | Druckausg.: 978-3-319-14010-0 LOC classification:
  • QC1-999
DOI: DOI: 10.1007/978-3-319-14011-7Online resources:
Summary: This book focuses on the new possibilities and approaches to social modeling currently being made possible by an unprecedented variety of datasets generated by our interactions with modern technologies. This area has witnessed a veritable explosion of activity over the last few years, yielding many interesting and useful results. Our aim is to provide an overview of the state of the art in this area of research, merging an extremely heterogeneous array of datasets and models. Social Phenomena: From Data Analysis to Models is divided into two parts. Part I deals with modeling social behavior under normal conditions: How we live, travel, collaborate and interact with each other in our daily lives. Part II deals with societal behavior under exceptional conditions: Protests, armed insurgencies, terrorist attacks, and reactions to infectious diseases. This book offers an overview of one of the most fertile emerging fields bringing together practitioners from scientific communities as diverse as social sciences, physics and computer science. We hope to not only provide an unifying framework to understand and characterize social phenomena, but also to help foster the dialogue between researchers working on similar problems from different fields and perspectivesPPN: PPN: 1657894843Package identifier: Produktsigel: ZDB-2-PHA
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