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arXiv 1606.03386cs.SIphysics.soc-ph
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网络中产品增长的广义Bass模型

A Generalized Bass Model for Product Growth in Networks

Vahideh H. Manshadi, Sidhant Misra

摘要:

许多产品和创新通过人口中个体的社会互动而变得众所周知并被广泛采用。Bass扩散模型已被广泛用于模拟这种社会系统中收养的时间演变。在该模型中,新采用的可能性与以前采用者的数量成正比,隐含地假设网络中所有个体之间的全局(或同质)交互。然而,在许多大型社交网络中并不存在这样的全球互动。相反,个体通常与较大群体的一小部分互动。为了量化有限交互网络中的增长率(或等效的采用时间),我们研究了一个随机采用过程,其中每个人采用的可能性与他/她交互的一小群人(而不是整个采用者群体)中的采用者数量成正比。当底层网络的相互作用是一个随机的$k$ -正则图,我们计算的样本路径限制的采用者的分数。我们证明了该极限与一个微分方程的解相一致,该微分方程可以看作是Bass扩散模型的推广。当度$k$是有界的,我们表明采用曲线显着不同的Bass扩散模型。特别是,采用率的增长速度比Bass模型预测的要慢。此外,采用曲线是不对称的,不像巴斯扩散模型。这种不对称性对市场潜力的估计有重要影响。最后,我们在更精细的尺度上计算早期采用的时间,例如,人口数量的对数。

英文摘要:

Many products and innovations become well-known and widely adopted through the social interactions of individuals in a population. The Bass diffusion model has been widely used to model the temporal evolution of adoption in such social systems. In the model, the likelihood of a new adoption is proportional to the number of previous adopters, implicitly assuming a global (or homogeneous) interaction among all individuals in the network. Such global interactions do not exist in many large social networks, however. Instead, individuals typically interact with a small part of the larger population. To quantify the growth rate (or equivalently the adoption timing) in networks with limited interactions, we study a stochastic adoption process where the likelihood that each individual adopts is proportional to the number of adopters among the small group of persons he/she interacts with (and not the entire population of adopters). When the underlying network of interactions is a random $k$-regular graph, we compute the sample path limit of the fraction of adopters. We show the limit coincides with the solution of a differential equation which can viewed as a generalization of the Bass diffusion model. When the degree $k$ is bounded, we show the adoption curve differs significantly from the one corresponds to the Bass diffusion model. In particular, the adoption grows more slowly than what the Bass model projects. In addition, the adoption curve is asymmetric, unlike that of the Bass diffusion model. Such asymmetry has important consequences for the estimation of market potential. Finally, we calculate the timing of early adoptions at finer scales, e.g., logarithmic in the population size.

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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