Social and spatial predictors of collective search behaviors
Abstract Understanding crowd behavior is critical for designing buildings and public spaces with efficient circulation. However, the interplay of social and spatial contexts makes this endeavor challenging. This paper examines scenarios in which crowds perform a search task with time constraints, ak...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-02460-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849688372426047488 |
|---|---|
| author | Marion Hoffman Tyler Thrash Christoph Hölscher Mubbasir Kapadia Victor R. Schinazi |
| author_facet | Marion Hoffman Tyler Thrash Christoph Hölscher Mubbasir Kapadia Victor R. Schinazi |
| author_sort | Marion Hoffman |
| collection | DOAJ |
| description | Abstract Understanding crowd behavior is critical for designing buildings and public spaces with efficient circulation. However, the interplay of social and spatial contexts makes this endeavor challenging. This paper examines scenarios in which crowds perform a search task with time constraints, akin to individuals shopping or officers searching a crime area. We formulate and test two sets of hypotheses defined at the crowd and individual levels using desktop VR experiments. We conducted four experimental sessions that employed different social incentives (collaborative versus competitive) with a total of 140 participants, using a mixed factorial design where each individual participated in 12 trials. We found that competitive incentives produced higher levels of crowd aggregation than collaborative incentives. In addition, individuals were more likely to be influenced by others’ behaviors in the collaborative compared to the competitive condition. Notably, these social signals were conveyed among participants without any verbal communication. We also developed a novel graph theoretic measure, “search attractiveness,” that accurately predicts space occupation during a search task. This paper highlights the roles of social and spatial contexts in understanding occupation and aggregation. |
| format | Article |
| id | doaj-art-a0c81b5e67654e759ec57bf2c82619b4 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-a0c81b5e67654e759ec57bf2c82619b42025-08-20T03:22:02ZengNature PortfolioScientific Reports2045-23222025-05-0115111610.1038/s41598-025-02460-7Social and spatial predictors of collective search behaviorsMarion Hoffman0Tyler Thrash1Christoph Hölscher2Mubbasir Kapadia3Victor R. Schinazi4Institute for Advanced Study in Toulouse, Toulouse School of Economics, University Toulouse CapitoleDepartment of Biology, Saint Louis UniversityDepartment of Humanities, Social and Political Sciences, ETH ZürichDepartment of Computer Science, Rutgers UniversityDepartment of Humanities, Social and Political Sciences, ETH ZürichAbstract Understanding crowd behavior is critical for designing buildings and public spaces with efficient circulation. However, the interplay of social and spatial contexts makes this endeavor challenging. This paper examines scenarios in which crowds perform a search task with time constraints, akin to individuals shopping or officers searching a crime area. We formulate and test two sets of hypotheses defined at the crowd and individual levels using desktop VR experiments. We conducted four experimental sessions that employed different social incentives (collaborative versus competitive) with a total of 140 participants, using a mixed factorial design where each individual participated in 12 trials. We found that competitive incentives produced higher levels of crowd aggregation than collaborative incentives. In addition, individuals were more likely to be influenced by others’ behaviors in the collaborative compared to the competitive condition. Notably, these social signals were conveyed among participants without any verbal communication. We also developed a novel graph theoretic measure, “search attractiveness,” that accurately predicts space occupation during a search task. This paper highlights the roles of social and spatial contexts in understanding occupation and aggregation.https://doi.org/10.1038/s41598-025-02460-7Crowd dynamicsSpatial layoutVirtual reality experimentsGraph theorySpace syntax |
| spellingShingle | Marion Hoffman Tyler Thrash Christoph Hölscher Mubbasir Kapadia Victor R. Schinazi Social and spatial predictors of collective search behaviors Scientific Reports Crowd dynamics Spatial layout Virtual reality experiments Graph theory Space syntax |
| title | Social and spatial predictors of collective search behaviors |
| title_full | Social and spatial predictors of collective search behaviors |
| title_fullStr | Social and spatial predictors of collective search behaviors |
| title_full_unstemmed | Social and spatial predictors of collective search behaviors |
| title_short | Social and spatial predictors of collective search behaviors |
| title_sort | social and spatial predictors of collective search behaviors |
| topic | Crowd dynamics Spatial layout Virtual reality experiments Graph theory Space syntax |
| url | https://doi.org/10.1038/s41598-025-02460-7 |
| work_keys_str_mv | AT marionhoffman socialandspatialpredictorsofcollectivesearchbehaviors AT tylerthrash socialandspatialpredictorsofcollectivesearchbehaviors AT christophholscher socialandspatialpredictorsofcollectivesearchbehaviors AT mubbasirkapadia socialandspatialpredictorsofcollectivesearchbehaviors AT victorrschinazi socialandspatialpredictorsofcollectivesearchbehaviors |