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arXiv 0903.2533physics.soc-ph
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社会科学中长尾分布的演化模型

An evolutionary model of long tailed distributions in the social sciences

R. Alexander Bentley, Paul Ormerod, Michael Batty

摘要:

社会科学中对人类集体行为的研究,往往以个人行为的细节为基础,从物理科学中提供了许多关于优雅统计学的“社会”模型。借鉴社会影响力的行为研究,我们提出了一个简约的随机模型,它产生了一个完整的家庭的现实世界的右偏社会经济分布,包括指数,赢家通吃,幂律尾的不同指数和幂律在整个数据。被广泛使用的阿尔伯特-巴拉巴西偏好依恋模型只是这个更普遍的模型的一个特例。此外,该模型产生的连续营业额在这些分布内观察经验。先前的偏好依恋模型已经产生了特定的分布与营业额使用任意的附加规则,但营业额是我们的模型的固有特征。该模型还复制了一个有趣的新关系,在一系列实证研究中观察到,幂律指数和所代表的数据比例之间。

英文摘要:

Studies of collective human behavior in the social sciences, often grounded in details of actions by individuals, have much to offer `social' models from the physical sciences concerning elegant statistical regularities. Drawing on behavioral studies of social influence, we present a parsimonious, stochastic model, which generates an entire family of real-world right-skew socio-economic distributions, including exponential, winner-take-all, power law tails of varying exponents and power laws across the whole data. The widely used Albert-Barabasi model of preferential attachment is simply a special case of this much more general model. In addition, the model produces the continuous turnover observed empirically within those distributions. Previous preferential attachment models have generated specific distributions with turnover using arbitrary add-on rules, but turnover is an inherent feature of our model. The model also replicates an intriguing new relationship, observed across a range of empirical studies, between the power law exponent and the proportion of data represented.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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