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Journal of Computational Social Science [electronic resource] / edited by Takashi Kamihigashi.

Contributor(s): Material type: Continuing resourcePublisher: Singapore : Springer Nature Singapore : Imprint: Springer.Description: online resourceISSN:
  • 2432-2725
Subject(s): Additional physical formats: Printed version: : No titleOnline resources: Summary: The Journal of Computational Social Science (JCSS) is an interdisciplinary peer-reviewed journal that ties together groundbreaking research across the strata of the social sciences (sociology, economics, political science, psychology, linguistics, and other disciplines), physics, biology, management science, computer science, and data science. In addition to topics conventionally associated with computational social science, the journal invites contributions that analyze social/ economic phenomena or structures using computational approaches related to, but not restricted to, the following methods or fields: complex systems, economic modeling, econophysics, financial networks, risk management, urban planning, transportation analysis, artificial intelligence, image processing, text analytics, computational linguistics, numerical optimization, simulation-based statistical inference, and high-performance computing. We invite contributions from researchers in any field who analyze social/ economic phenomena or structures based on large-scale data, simulations, or other computational approaches.
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The Journal of Computational Social Science (JCSS) is an interdisciplinary peer-reviewed journal that ties together groundbreaking research across the strata of the social sciences (sociology, economics, political science, psychology, linguistics, and other disciplines), physics, biology, management science, computer science, and data science. In addition to topics conventionally associated with computational social science, the journal invites contributions that analyze social/ economic phenomena or structures using computational approaches related to, but not restricted to, the following methods or fields: complex systems, economic modeling, econophysics, financial networks, risk management, urban planning, transportation analysis, artificial intelligence, image processing, text analytics, computational linguistics, numerical optimization, simulation-based statistical inference, and high-performance computing. We invite contributions from researchers in any field who analyze social/ economic phenomena or structures based on large-scale data, simulations, or other computational approaches.

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