TY - GEN
T1 - Group affect in complex decision-making
T2 - 10th International Conference on Computational Collective Intelligence, ICCCI 2018
AU - Chohra, Amine
AU - Madani, Kurosh
AU - van der Wal, Chantal Natalie
PY - 2018
Y1 - 2018
N2 - Integrating affect in both individual and collective decision-making processes in order to solve real-world problems can be challenging. This research aims to: (1) investigate how group affect (moods, emotions, and feelings) can be integrated and formalized in the decision-making processes; (2) develop current practices; and (3) draw ideas for future perspectives and real-world applications. For this purpose, the role of affect in decision-making is investigated on the individual behavior level, emotional intelligence, and the collective behavior level. The used methodology consists of exploring and investigating the main characteristics developed in group affect in complex decision-making systems from psychology to computer science. From this, a common global structure is deduced: individual processes, group processes and emerging processes (bottom-up, top-down, and combination of bottom-up and top-down components). Following this, one psychological model and two computational models of group emotion and decision are analyzed, and discussed. Their different approaches to developing the main characteristics of a computational model integrating group affect in the decision-making process are highlighted. Finally, specific scenarios of real-world applications are presented in order to draw interesting and promising computational model perspectives.
AB - Integrating affect in both individual and collective decision-making processes in order to solve real-world problems can be challenging. This research aims to: (1) investigate how group affect (moods, emotions, and feelings) can be integrated and formalized in the decision-making processes; (2) develop current practices; and (3) draw ideas for future perspectives and real-world applications. For this purpose, the role of affect in decision-making is investigated on the individual behavior level, emotional intelligence, and the collective behavior level. The used methodology consists of exploring and investigating the main characteristics developed in group affect in complex decision-making systems from psychology to computer science. From this, a common global structure is deduced: individual processes, group processes and emerging processes (bottom-up, top-down, and combination of bottom-up and top-down components). Following this, one psychological model and two computational models of group emotion and decision are analyzed, and discussed. Their different approaches to developing the main characteristics of a computational model integrating group affect in the decision-making process are highlighted. Finally, specific scenarios of real-world applications are presented in order to draw interesting and promising computational model perspectives.
KW - Affect (moods, emotions, feelings)
KW - Complex systems
KW - Computer science
KW - Individual and collective decision-making
KW - Psychology
UR - http://www.scopus.com/inward/record.url?scp=85053136657&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85053136657&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-98446-9_21
DO - 10.1007/978-3-319-98446-9_21
M3 - Conference contribution
AN - SCOPUS:85053136657
SN - 9783319984452
VL - 2
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 222
EP - 233
BT - Computational Collective Intelligence
A2 - Nguyen, Ngoc Thanh
A2 - Trawinski, Bogdan
A2 - Pimenidis, Elias
A2 - Khan, Zaheer
PB - Springer/Verlag
Y2 - 5 September 2018 through 7 September 2018
ER -
