2016
DOI: 10.3389/fphy.2016.00037
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Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science

Abstract: The interest of physicists in economic and social questions is not new: during the last decades, we have witnessed the emergence of what is formally called nowadays sociophysics [1] and econophysics [2] that can be grouped into the common term "Interdisciplinary Physics" along with biophysics, medical physics, agrophysics, etc. With tools borrowed from statistical physics and complexity science, among others, these areas of study have already made important contributions to our understanding of how humans orga… Show more

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Cited by 5 publications
(2 citation statements)
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“…An extensive literature review failed to find any work grounded in a systems thinking approach, adopting a data-driven approach that also leverages Artificial Intelligence (AI) based techniques for developing a knowledge model for WE systems. The advent of big data, machine learning, and AI has opened new ways to approach research in social science [2][3][4][5][6] and this has been exclusively addressed through the interdisciplinary domain of Computational Social Science (CSS). CSS can be explained as a specific subcategory of work on big data [7], and the philosophical foundations of this new field have been discussed by S. Benthall [8].…”
Section: Introductionmentioning
confidence: 99%
“…An extensive literature review failed to find any work grounded in a systems thinking approach, adopting a data-driven approach that also leverages Artificial Intelligence (AI) based techniques for developing a knowledge model for WE systems. The advent of big data, machine learning, and AI has opened new ways to approach research in social science [2][3][4][5][6] and this has been exclusively addressed through the interdisciplinary domain of Computational Social Science (CSS). CSS can be explained as a specific subcategory of work on big data [7], and the philosophical foundations of this new field have been discussed by S. Benthall [8].…”
Section: Introductionmentioning
confidence: 99%
“…In borrowing computation approaches, we should not discard theory. Otherwise put, when borrowing the computational approach, we cannot indiscriminately adopt the purely signal recognition or inductive method (Borge‐Holthoefer, Moreno, & Yasseri, ). Rather, we need to combine induction with deduction, following the famous recommendation of Francis Bacon () in The New Organon to advance toward true knowledge through semi‐induction, which is empirical detection of patterns steered and mitigated by theoretical assumptions.…”
Section: Introduction: What Is Computational Communication Research?mentioning
confidence: 99%