Contagion and Interpersonal Influence: Distinguishing Mechanisms of Behavior Change Using Social Network Theory.

Connections (Toronto, Ont.) Pub Date : 2024-01-01 Epub Date: 2024-08-20 DOI:10.21307/connections-2019.041
Thomas W Valente
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Abstract

The present paper articulates the many ways social network researchers conceptualize and operationalize network influences on people's behaviors. Four categories of network influences are described: (1) personal network, (2) positional, (3) network-level, and (4) individual network-level interactions. Personal network effects are based on data from the individual's direct and indirect contacts. Positional effects are derived from the individual's position in the network such as being central or peripheral. Network-level effects are measured using network-level indicators such as centralization or clustering. Interaction effects occur when there is consideration of both the individual and network level measures such as understanding the influence of being in a central position in a centralized or decentralized network. These various network effects are contrasted with contagion, which is the most frequently used mechanism for diffusion. One conclusion drawn from this review is that when we invoke contagion explanations, we give agency to the product, whereas when we invoke interpersonal influence explanations, we give agency to people and social systems.

传染与人际影响:运用社会网络理论区分行为改变的机制。
本文阐述了社会网络研究者概念化和操作化网络对人们行为影响的多种方式。本文描述了四类网络影响:(1)个人网络,(2)位置网络,(3)网络层面,(4)个人网络层面的互动。个人网络效应基于个人直接和间接接触的数据。位置效应来源于个体在网络中的位置,如中心或外围。使用网络级指标(如集中化或集群化)来测量网络级效应。当考虑到个人和网络层面的措施时,例如理解在集中或分散的网络中处于中心位置的影响,就会产生交互效应。这些不同的网络效应与传染形成对比,传染是最常用的扩散机制。从这篇综述中得出的一个结论是,当我们援引传染解释时,我们赋予了产品代理权,而当我们援引人际影响解释时,我们赋予了人和社会系统代理权。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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