Mosleh Mohsen, Eckles Dean, Rand David G
Oxford Internet Institute, Social Sciences Division, University of Oxford, Oxford OX1 3JS, United Kingdom.
Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA 02142.
Proc Natl Acad Sci U S A. 2025 Jul 8;122(27):e2404590122. doi: 10.1073/pnas.2404590122. Epub 2025 Jun 30.
Empirical social networks are characterized by a high degree of triadic closure (i.e., transitivity, clustering): network neighbors of the same individual are also likely to be directly connected. It is unknown to what degree this results from dispositions to form such ties (i.e., to close open triangles) per se versus other processes such as homophily and more opportunities for exposure. These mechanisms are difficult to disentangle in many settings. On social media, however, they can be decomposed - and platforms frequently make decisions that depend on these distinct processes. Here, using a field experiment on social media, we randomize the existing network structure that a user faces when they are followed by a target account that we control. We then examine whether the user reciprocates this tie formation. Being randomly assigned to have an existing tie to an account that follows the target user increases tie formation by 35%. Through multiple control conditions, we attribute this effect specifically to a minimal cue that indicates the presence of a potential mutual follower. Theory suggests that triadic closure should be especially likely in open triads of strong ties, and accordingly we find larger effects when the subject has interacted more with the existing follower. These results indicate a substantial role for tendencies toward triadic closure, but one that is substantially smaller than what might be inferred from prior observational studies. Platforms and others may rely on these tendencies in encouraging tie formation, with broader implications for network structure and information diffusion in online networks.
经验性社会网络的特点是具有高度的三元闭包（即传递性、聚类性）：同一个人的网络邻居也很可能直接相连。目前尚不清楚这种情况在多大程度上是由于形成此类联系的倾向（即封闭开放三角形）本身，还是由于其他过程，如同质性和更多的接触机会。在许多情况下，这些机制很难区分。然而，在社交媒体上，它们可以被分解——而且平台经常做出依赖于这些不同过程的决策。在这里，我们通过一项社交媒体实地实验，对用户在被我们控制的目标账户关注时所面对的现有网络结构进行随机化处理。然后我们检查用户是否回应这种联系的形成。被随机分配与关注目标用户的账户建立现有联系，会使联系形成增加35%。通过多个控制条件，我们将这种效应具体归因于一个表明潜在共同关注者存在的最小线索。理论表明，三元闭包在强联系的开放三元组中应该尤其可能出现，因此我们发现当主体与现有关注者互动更多时，效应更大。这些结果表明三元闭包倾向发挥了重要作用，但比先前观察性研究所推断的要小得多。平台和其他方面可能会依赖这些倾向来鼓励联系的形成，这对在线网络中的网络结构和信息传播具有更广泛的影响。
