Computing agents' reputation within a network
提出一个利用投资组合理论和期权结构在社交网络中传递信息和建立声誉的模型，通过多轮通信聚合估计值，并给出达成共识或两极分化的条件。
We propose a model of information transmission and reputation building within a social network that exploits portfolio theory and option structures. The network aims to estimate an unknown parameter through multiple communication rounds. At every communication round, estimates of different agents' abilities are shared, avoiding the repetition of information. These estimates are interpreted as financial assets driven by a compound Poisson process. After every communication round, agents construct a fictitious portfolio of options whose underlying is the vector of shared estimates. The portfolio's weights are exploited to aggregate the information received in the communication round. Sufficient conditions for reaching consensus or polarization are provided. • A social network has a multi-dimensional informative content. • Multiple rounds of communication do not imply repetition of information. • A model is devised that uses option structures and portfolio theory to assign weights to agents. • Practical examples show that the model leads to results consistent with intuition and common sense. • The unidimensionality of opinions, under mild conditions, is preserved with a non-homogeneous Markov chain.