An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers

L. Medeiros, C. Natalie van der Wal

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Airline passengers can get stranded in an airport due to a number of reasons. As a consequence, they might get frustrated. Frustration leads to misbehaving if a given individual is frustrated enough, says the literature. In this work, an agent-based model of stranded passengers in an airport departure area is presented. Structured simulations show how personal and environmental characteristics such as age, gender and emotional contagion, among others, influence the frustration dynamics, number and type of misbehaviours in such a scenario. We also present simulation results with two implemented support models (a chatbot and multilingual staff) aiming to reduce the overall frustration level of passengers facing this type of situation. Important findings are that: men are more likely to use force then women, the crowd composition plays an important role in terms of misbehaviours, the effect of emotional contagion leads to more misbehaviours and a chatbot might be considered as an alternative for supporting stranded passengers.
LanguageEnglish
Title of host publicationProceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017)
PublisherSpringer LNCS
Pages28
Number of pages40
StateAccepted/In press - 1 Jun 2017

Fingerprint

Airports
Chemical analysis

Keywords

  • Computational modelling
  • Multi-agent based modelling
  • Emotional contagion
  • Misbehaviour prediction
  • Crime prevention
  • Chatbots

Cite this

Medeiros, L., & van der Wal, C. N. (Accepted/In press). An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers. In Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017) (pp. 28). Springer LNCS.
Medeiros, L. ; van der Wal, C. Natalie. / An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers. Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017). Springer LNCS, 2017. pp. 28
@inproceedings{92ca83b8b3e241749b9222f8669d839f,
title = "An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers",
abstract = "Airline passengers can get stranded in an airport due to a number of reasons. As a consequence, they might get frustrated. Frustration leads to misbehaving if a given individual is frustrated enough, says the literature. In this work, an agent-based model of stranded passengers in an airport departure area is presented. Structured simulations show how personal and environmental characteristics such as age, gender and emotional contagion, among others, influence the frustration dynamics, number and type of misbehaviours in such a scenario. We also present simulation results with two implemented support models (a chatbot and multilingual staff) aiming to reduce the overall frustration level of passengers facing this type of situation. Important findings are that: men are more likely to use force then women, the crowd composition plays an important role in terms of misbehaviours, the effect of emotional contagion leads to more misbehaviours and a chatbot might be considered as an alternative for supporting stranded passengers.",
keywords = "Computational modelling, Multi-agent based modelling, Emotional contagion, Misbehaviour prediction, Crime prevention, Chatbots",
author = "L. Medeiros and {van der Wal}, {C. Natalie}",
year = "2017",
month = "6",
day = "1",
language = "English",
pages = "28",
booktitle = "Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017)",
publisher = "Springer LNCS",

}

Medeiros, L & van der Wal, CN 2017, An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers. in Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017). Springer LNCS, pp. 28.

An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers. / Medeiros, L.; van der Wal, C. Natalie.

Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017). Springer LNCS, 2017. p. 28.

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers

AU - Medeiros,L.

AU - van der Wal,C. Natalie

PY - 2017/6/1

Y1 - 2017/6/1

N2 - Airline passengers can get stranded in an airport due to a number of reasons. As a consequence, they might get frustrated. Frustration leads to misbehaving if a given individual is frustrated enough, says the literature. In this work, an agent-based model of stranded passengers in an airport departure area is presented. Structured simulations show how personal and environmental characteristics such as age, gender and emotional contagion, among others, influence the frustration dynamics, number and type of misbehaviours in such a scenario. We also present simulation results with two implemented support models (a chatbot and multilingual staff) aiming to reduce the overall frustration level of passengers facing this type of situation. Important findings are that: men are more likely to use force then women, the crowd composition plays an important role in terms of misbehaviours, the effect of emotional contagion leads to more misbehaviours and a chatbot might be considered as an alternative for supporting stranded passengers.

AB - Airline passengers can get stranded in an airport due to a number of reasons. As a consequence, they might get frustrated. Frustration leads to misbehaving if a given individual is frustrated enough, says the literature. In this work, an agent-based model of stranded passengers in an airport departure area is presented. Structured simulations show how personal and environmental characteristics such as age, gender and emotional contagion, among others, influence the frustration dynamics, number and type of misbehaviours in such a scenario. We also present simulation results with two implemented support models (a chatbot and multilingual staff) aiming to reduce the overall frustration level of passengers facing this type of situation. Important findings are that: men are more likely to use force then women, the crowd composition plays an important role in terms of misbehaviours, the effect of emotional contagion leads to more misbehaviours and a chatbot might be considered as an alternative for supporting stranded passengers.

KW - Computational modelling

KW - Multi-agent based modelling

KW - Emotional contagion

KW - Misbehaviour prediction

KW - Crime prevention

KW - Chatbots

M3 - Conference contribution

SP - 28

BT - Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017)

PB - Springer LNCS

ER -

Medeiros L, van der Wal CN. An Agent-based Model Predicting Group Emotion and Misbehaviours in Stranded Passengers. In Proceedings of 18th EPIA Conference on Artificial Intelligence (EPIA 2017). Springer LNCS. 2017. p. 28.