@article{fdi:010084768,
  title = {{G}eneration of synthetic populations in social simulations : a review of methods and practices},
  author = {{C}hapuis, {K}evin and {T}aillandier, {P}atrick and {D}rogoul, {A}lexis},
  editor = {},
  language = {{ENG}},
  abstract = {{T}o build realistic models of social systems, designers of agent-based models tend to incorporate a considerable amount of data, which influence the model outcomes. {D}ata concerning the attributes of social agents, which compose synthetic populations, are particularly important but usually difficult to collect and therefore use in simulations. {I}n this paper, we have reviewed state of the art methodologies and theories for building realistic synthetic populations for agent-based simulation models and practices in social simulations. {W}e also highlight the discrepancies between theory and practice and outline the challenges in bridging this gap through a quantitative and narrative review of work published in {JASSS} between 2011 and 2021. {F}inally, we present several recommendations that could help modellers adopt best practices for synthetic population generation.},
  keywords = {{S}ynthetic {P}opulation ; {A}gent-{B}ased {S}imulation ; {M}odel {I}nitialization ; {D}ata-{D}riven {S}ocial {S}imulation},
  booktitle = {},
  journal = {{JASSS} : the {J}ournal of {A}rtificial {S}ocieties and {S}ocial {S}imulation},
  volume = {25},
  numero = {2},
  pages = {6 [23 ]},
  ISSN = {1460-7425},
  year = {2022},
  DOI = {10.18564/jasss.4762},
  URL = {https://www.documentation.ird.fr/hor/fdi:010084768},
}