Author, as appears in the article.: Poux-Medard, Gael; Cobo-Lopez, Sergio; Duch, Jordi; Guimera, Roger; Sales-Pardo, Marta
Department: Enginyeria Química
URV's Author/s: Cobo Lopez, Sergio / Duch Gavaldà, Jordi / Guimera Manrique, Roger / Sales Pardo, Marta
Keywords: Stochastic block model Prediction Persistence Human behavior Decision making process Choice mechanisms Blockmodels
Abstract: Many studies have shown that there are regularities in the way human beings make decisions. However, our ability to obtain models that capture such regularities and can accurately predict unobserved decisions is still limited. We tackle this problem in the context of individuals who are given information relative to the evolution of market prices and asked to guess the direction of the market. We use a networks inference approach with stochastic block models (SBM) to find the model and network representation that is most predictive of unobserved decisions. Our results suggest that users mostly use recent information (about the market and about their previous decisions) to guess. Furthermore, the analysis of SBM groups reveals a set of strategies used by players to process information and make decisions that is analogous to behaviors observed in other contexts. Our study provides and example on how to quantitatively explore human behavior strategies by representing decisions as networks and using rigorous inference and model-selection approaches.
Thematic Areas: Social sciences, mathematical methods Modeling and simulation Mathematics, interdisciplinary applications Engenharias iv Engenharias i Computer science applications Computational mathematics Ciencias sociales Ciência da computação
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: sergio.cobo@urv.cat roger.guimera@urv.cat jordi.duch@urv.cat marta.sales@urv.cat
Author identifier: 0000-0002-3597-4310 0000-0003-2639-6333 0000-0002-8140-6525
Record's date: 2024-10-19
Journal volume: 10
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-021-00280-z
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Epj Data Science. 10 (1): 26-
APA: Poux-Medard, Gael; Cobo-Lopez, Sergio; Duch, Jordi; Guimera, Roger; Sales-Pardo, Marta (2021). Complex decision-making strategies in a stock market experiment explained as the combination of few simple strategies. Epj Data Science, 10(1), 26-. DOI: 10.1140/epjds/s13688-021-00280-z
Article's DOI: 10.1140/epjds/s13688-021-00280-z
Entity: Universitat Rovira i Virgili
Journal publication year: 2021
Publication Type: Journal Publications