Programming collective intelligence
Programming collective intelligence
Predicting positive and negative links in online social networks
Proceedings of the 19th international conference on World wide web
A statistical approach to the representation of uncertainty in beliefs using spread of opinions
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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The authors study patterns about group opinions in a group-based society by considering social influence. They classify three types of social influence: positive, neutral, and negative from the perspective of social identity, and investigate to what extent the non-positive social influence leads to group opinion polarization based on the Hopfield network model. Numerical simulations show that opinion in a group-based society would self-organize into bi-polarization pattern under the condition of no imposing external intervention, which is entirely different from the result of drift to an extreme polarization dominant state with single homogenous influence. These results are explained in the study and the authors show that opinions polarization in a group is coexisted with local structure balance.