An Extension of Social Network Group Decision-Making Based on TrustRank and Personas

DOI

10.2991/ijcis.d.200310.001How to use a DOI?

Keywords

Social network; PageRank; TrustRank; Persona; Social network group decision-making (SN-GDM)

Abstract

With the development of social networking big data, social network group decision-making (SN-GDM) has been widely applied in many fields. This paper focuses on three main components: (1) the determination of the decision makers' (DMs) weights based on different social influence; (2) the anti-deception mechanism; and (3) the persona method. We introduce the TrustRank algorithm and the persona method into SN-GDM. Based on the TrustRank algorithm, both trusted and deceptive DMs in a seed set are artificially identified and given initial static scores to derive the influence of each DM. Additionally, the persona method is introduced to cluster DMs and achieve personalized decision-making. Further, we present a numerical example and comparison to demonstrate the efficiency of the framework in coping with non-socially shared preferences in SN-GDM. As expected, our findings indicate that our framework reduces the influence of deceptive DMs on the decision results.

Copyright

© 2020 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Mei Cai
AU  - Yiming Wang
AU  - Zaiwu Gong
PY  - 2020
DA  - 2020/03/17
TI  - An Extension of Social Network Group Decision-Making Based on TrustRank and Personas
JO  - International Journal of Computational Intelligence Systems
SP  - 332
EP  - 340
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200310.001
DO  - 10.2991/ijcis.d.200310.001
ID  - Cai2020
ER  -