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[目的 /意义]通过微观层面上个体的因果相互作用来阐述信息计量领域宏观幂律分布现象形成的必然性,将其从随机性的统计规律转变成为必然性的动力学规律。[方法 /过程]在幂律分布必然性的揭示上,抛弃粗糙的机械还原论视角,而将其放在更加精密的复杂系统的分析框架下。数学论证上以普赖斯引文网络为实例,运用主方程、隐马尔科夫链推导出双参数广义普赖斯定理β函数数学描述并进一步推导出3条数学性质。[结果/结论]将信息计量领域普遍存在的偏态随机性统计规律发展成为确定性的系统动力学规律,即在简单线性累加优势规则而非马太效应规则的约束下,通过最细粒度层级上的因果二元组的多次正向性互动反馈,经由临界涨落和对称性打破,根据严谨的网络动力学数学语言描述出系统的自组织有序性稳态建构。
[Purpose / Significance] The inevitability of the formation of the phenomenon of macroscopic power-law distribution in the field of information measurement is illustrated through the causal interaction of individuals at the micro level, and it is transformed from the statistical law of randomness to the law of inevitability. [Methods / Processes] Discarding the rough perspective of mechanical reductionism on the disclosure of the inequality of power law distribution puts it in the framework of a more sophisticated complex system analysis. On the mathematical proofs, this paper uses the Price Rice citation network as an example to derive the mathematical description of the β-function of the two-parameter generalized Price theorem and further derive three mathematical properties by using the main equation and the hidden Markov chain. [Results / Conclusions] The ubiquitous statistical rule of skewness in the field of information measurement has been developed into a deterministic system law of dynamics, that is, by the simplest linear additive superiority rules rather than the Matthew effect rules, On the basis of rigorous network dynamics mathematical language, this paper describes the self-organized and orderly steady state construction of the system through multiple forward positive feedbacks of causal binary groups on the basis of critical fluctuation and symmetry.