Modeling social interactions: Identification, empirical methods and policy implications
Modeling social interactions: Identification, empirical methods and policy implications
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DOI：
10.1007/s11002-008-9048-z
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发表时间：
2008-12-01
影响因子：
3.6
通讯作者：
Tucker, Catherine E.
中科院分区：
文献类型：
--
作者：
Hartmann, Wesley R.;Manchanda, Puneet;Tucker, Catherine E.
当网络中的代理人直接影响其他代理人的选择时，社会互动就会发生，而不是通过市场中介。对这种相互作用及其结果的研究长期以来一直是各种社会科学感兴趣的领域。随着促进和记录这种互动的电子媒体的出现，这种兴趣在商业世界中也急剧增长。在本文中，我们提供了一个简短的总结，到目前为止已知的，讨论了对这一领域感兴趣的研究人员的主要挑战，并提供了一个共同的词汇，希望能产生未来（跨学科）的研究。本文认为，区分实际的因果关系的社会相互作用，从其他现象，可能会导致因果关系的错误推断的挑战。此外，我们区分了两种广泛定义的社交互动类型，它们与互动在网络中传播的强度有关。我们还提供了一个非常有选择性的审查，如何从其他学科的见解可以改善和通知建模选择。最后，我们讨论了如何使用社交互动模型为营销政策提供指导，并总结了对未来研究方向的看法。
Social interactions occur when agents in a network affect other agents' choices directly, as opposed to via the intermediation of markets. The study of such interactions and the resultant outcomes has long been an area of interest across a wide variety of social sciences. With the advent of electronic media that facilitate and record such interactions, this interest has grown sharply in the business world as well. In this paper, we provide a brief summary of what is known so far, discuss the main challenges for researchers interested in this area, and provide a common vocabulary that will hopefully engender future (cross disciplinary) research. The paper considers the challenges of distinguishing actual causal social interactions from other phenomena that may lead to a false inference of causality. Further, we distinguish between two broadly defined types of social interactions that relate to how strongly interactions spread through a network. We also provide a very selective review of how insights from other disciplines can improve and inform modeling choices. Finally, we discuss how models of social interaction can be used to provide guidelines for marketing policy and conclude with thoughts on future research directions.