Experiments and models for human decision-making: social dilemmas, pedestrian movement and financial markets

• Autores: Mario Gutiérrez Roig
• Directores de la Tesis: Jaume Masoliver García (dir. tes.), Josep Perelló Palou (dir. tes.)
• Lectura: En la Universitat de Barcelona ( España ) en 2016
• Idioma: inglés
• Tribunal Calificador de la Tesis: Tobias Preis (presid.), M. Angeles Serrano Moral (secret.), Andy Kaltenbrunner (voc.)
• Programa de doctorado: Programa Oficial de Doctorado en Física
• Materias:
  • Matemáticas
    • Estadística
      • Teoría estocástica y análisis de series temporales
  • Física
    • Mecánica
      • Mecánica de sólidos
  • Psicología
    • Psicología experimental
      • Análisis experimental de la conducta
  • Sociología
    • Sociología matemática
      • Elaboración de modelos
• Enlaces
  • Tesis en acceso abierto en: Dipòsit Digital de la UB
• Resumen

  • The revolution of ICT technologies in Digital Era combined with progress of Complexity Sciences have lead to an emergence of Computational Social Science, whose purpose is to analyze society in a quantitative way. Physics, can provide some tools in such endeavor. Here, a new experimental framework called Pop-Up Experiments, based in Citizen Science philosophy and scientific rigor of Behavioral Experiments, is proposed. Experiments and mathematical models in agreement with them are used to validate to explain stylized facts of social phenomena concerning three different areas regarding human decision-making: Social Dilemmas, Pedestrian Movement and Financial Markets. In first place, two experiments are carried out on a variety of Social Dilemmas. Results demonstrate that children present a more volatile and random behavior than adults and the fact that individuals can be assigned to a small number of behavioral phenotypes. Secondly, pedestrian movement of visitors in a out-door fair have also been empirically studied. A model based in Langevin Dynamics that includes orientation persistence and potential landscape is able to reproduce observed movement patterns. Moreover, such tested model is theoretically adapted for describing other related issues like searching patterns. Finally, an experiment on human behavior with financial data, where participants try to anticipate real price series, reveals that under high uncertain environment humans develop intuitive strategies that ease them to make decisions. One of such strategies that consist in imitating what the price did before. The existence of such strategy in reality is afterwards confirmed by using Mutual Information and Transfer of Entropy analysis in Big Data recordings of clients performance of certain investment firm. In summary, all these experiences demonstrate that stochastic models and mathematical tools belonging to physics combined with Pop-Up Experiments constitute a very powerful tool at the service of Computational Social Science for the study of human decision-making. The impact of such fact-based approach models is can be important in promoting cooperative environments in educational process, redesigning spaces to allow a better mobility in areas like fairs or understanding how people manage their investments to establish better financial market policies.