Kashif Zia, Umar Farooq, Alois Ferscha,
"When the Wisdom of Crowd is Able to Overturn an Unpopular Norm? Lessons Learned from an Agent-Based Simulation"
: SIGSIM-PADS '21: Proceedings of the 2021 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation, ACM DL, Seite(n) 69-79, 5-2021
Original Titel:
When the Wisdom of Crowd is Able to Overturn an Unpopular Norm? Lessons Learned from an Agent-Based Simulation
Sprache des Titels:
Englisch
Original Buchtitel:
SIGSIM-PADS '21: Proceedings of the 2021 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation
Original Kurzfassung:
A model of bystanders' effect on volunteering (in case of an observed crime or critical situation) is extended to incorporate the possibility of a sense of guilt (after nonintervention). Based on sound theoretical and experimental foundations, an existing model of the spread of unpopular norms is used to allow dispersion of an unpopular norm (a mild crime) so that a population of agents may follow or accept it. The question asked is why a society (as a whole) is not able to overturn an unpopular norm through interventions. An agent-based model is proposed which captures all necessary ingredients to explore this question. Several what-if questions are asked by varying simulation parameters. The model and simulation reveal that a sense of guilt of bystanders improves the volunteering tendency. The simulation results also provide pieces of evidence of clear differentiation between the individual and societal perception of a crime. Through the simulation results, we were able to conclude that guilt, not only, improves the volunteering tendency, but also, very clearly differentiates between the individual and societal perception of an unpopular norm. Overall, it was learned that people intervene only when they are able to overcome the inhibitions of the crowd. However, even interventions do not guarantee to overturn an unpopular norm. In fact, irrespective of the state of interventions, there is no neutralization without guilt.