The scope of computational social science
Bibliographic Data
| ID | 20079904 |
|---|---|
| Authors | Claudio Cioffi-Revilla, Claudio Cioffi‐revilla (corresponding author) |
| Year | 2021 |
| Pages | 17-32 |
| Publication date | 2021-11-10 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | CHAPTER |
| Venue | Handbook of Computational Social Science, Volume 1 (SOURCE_BOOK) |
| Publisher | Routledge (PUBLISHER • GB) |
| DOI | 10.4324/9781003024583-3 |
| OpenAlex | W3213503979 |
| ISBN | 9781003024583 |
| Language | EN |
| Citations received | 1 |
| References cited | 16 |
Computational social science (CSS) is a field that integrates the study of humans and groups at all scales through the formal methodology of computational and mathematical models. Its purpose is to advance scientific understanding of social phenomena using computation both as a conceptual and theoretical paradigm, based on information processing, and as a methodological tool. Recently, a restrictive version of CSS has been proposed, driven by “big data” from social media and progress in algorithms from computer science, eschewing theory, mathematical models, and computational simulations – which are other core areas of CSS. This chapter presents a comprehensive and balanced scope of CSS that is theoretically and methodologically guided by theory, enriched by analytical models, and enabled by computer simulations, all three drawing on empirical data, be it big or small. After comparing the restrictive approach to CSS to two insightful metaphors, this chapter presents CSS as (a) an empirical science seeking deep and testable knowledge, (b) an integrative social science of humans and groups, and (c) a computational science that uses computer and mathematical models to advance our understanding of human and social dynamics. The scope of CSS is defined by five areas that constitute its core and borderlands that straddle the boundaries of CSS and other fields, as illustrated by contemporary theory and research on complex crises
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| Unique citing works | 1 |
|---|---|
| Citations per year | 0,5 |
| Citation span | 2024 - 2024 (1) |
| Citation velocity | recent |
| Highly cited | No |