학술논문

Consensus Opinion Model in Online Social Networks Based on Influential Users
Document Type
Periodical
Source
IEEE Access Access, IEEE. 7:28436-28451 2019
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Social networking (online)
Analytical models
Aggregates
Social groups
Computational modeling
Linguistics
Telecommunications
Influential users
link analysis
opinion propagation
voter model
fuzzy methods
consensus model
online social networks
Language
ISSN
2169-3536
Abstract
A framework to consensus opinion model within a networked social group is put forward. The current research in opinion formation within the groups is largely based on the opinion aggregation of each user of the network. However, the consistency of users in aggregation, social power, and the impact of each individual user of the group for opinion formation are not considered. In this paper, we investigate a consensus opinion model in social groups based on the impact of influential users and aggregation methods. In order to reach the consensus model, we aggregate the users’ opinions. To maintain consistency, we propagate the opinion through the users to reach an agreement. This propagation will consider the influential users’ impacts that have a crucial effect on its process. A novel method is proposed to detect the influential users and opinion propagation based on them to derive the opinion toward the networked social group. In particular, we applied optimism and pessimism scores as the users’ personality to discover the influential users in the network. Considering that, we propagate the opinion based on two facts: 1) the impact of influential users, derived by the presence of an extremely confident individual in the network and 2) the impact of neighbors, induced by the presence of the users who have a connection with the current user. Then, we proposed the opinion aggregation of the group induced by the weighted averaging operator and fuzzy techniques. In order to evaluate the validity of the method, we used enormous data sets of Epinions and Etsy which are signed and unsigned, respectively.