@misc{10481/72454,
year = {2021},
url = {http://hdl.handle.net/10481/72454},
abstract = {A twofold personalized feedback mechanism is established
for consensus reaching in social network group decisionmaking
(SN-GDM). It consists of two stages: (1) generating the
trusted recommendation advice for individuals; and (2) producing
personalized adoption coefficient for reducing unnecessary
adjustment costs. This is achieved by means of a uninorm
interval-valued trust propagation operator to obtain indirect
trust. The trust relationship is used to generate personalized
recommendation advice based on the principle of ‘a recommendation
being more acceptable the higher the level of trust
it derives from’. An optimization model is built to minimise
the total adjustment cost of reaching consensus by determining
personalized feedback adoption coefficient based on individuals’
consensus levels. Consequently, the proposed twofold personalized
feedback mechanism achieves a balance between group
consensus and individual personality. An example to demonstrate
how the proposed twofold personalized feedback mechanism
works is included, which is also used to show its rationality by
comparison with the traditional feedback mechanism in GDM.},
organization = {National Natural Science Foundation of China (NSFC)	71971135	
71571166	
71910107002},
organization = {Spanish Government	PID2019-103880RB-I00/AEI/10.13039/501100011033},
publisher = {IEEE},
keywords = {Group decision making},
keywords = {Consensus},
keywords = {Social network},
keywords = {Uninorm interval trust propagation},
keywords = {Personalized feedback},
keywords = {Minimum cost},
title = {Two-Fold Personalized Feedback Mechanism for Social Network Consensus by Uninorm Interval Trust Propagation},
author = {Wu, Jian and Chiclana Parrilla, Francisco and Herrera Viedma, Enrique},
}