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Cited by 275

The DOI matches its Crossref record; 95 of the 95 references it cites were found in a registry or an index.

Collective behavior in animal groups: Theoretical models and empirical studies

Open access
Giardina, Irene·2008·HFSP Journal

Abstract

Collective phenomena in animal groups have attracted much attention in the last years, becoming one of the hottest topics in ethology. There are various reasons for this. On the one hand, animal grouping provides a paradigmatic example of self-organization, where collective behavior emerges in absence of centralized control. The mechanism of group formation, where local rules for the individuals lead to a coherent global state, is very general and transcends the detailed nature of its components. In this respect, collective animal behavior is a subject of great interdisciplinary interest. On the other hand, there are several important issues related to the biological function of grouping and its evolutionary success. Research in this field boasts a number of theoretical models, but much less empirical results to compare with. For this reason, even if the general mechanisms through which self-organization is achieved are qualitatively well understood, a quantitative test of the models assumptions is still lacking. New analysis on large groups, which require sophisticated technological procedures, can provide the necessary empirical data.

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Metadata

Authors
Giardina, I.
Venue
HFSP Journal
Published
2008-08
Volume
2
Issue
4
Pages
205-219
ISSN
  • 1955-205X (ISSN-L)
  • 1955-2068
OpenAlex
W1981425595
Cited by
275
References
95
FWCI
13.17
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Collective behavior in animal groups: Theoretical models and empirical studies. https://app.cochat.ai/papers/10.2976/1.2961038
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Giardina, I. (2008). Collective behavior in animal groups: Theoretical models and empirical studies. HFSP Journal. https://doi.org/10.2976/1.2961038

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.