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Social influence cannot be identified from purely observational data on social networks, because such influence is generically confounded with latent homophily, i.e., with a node's network partners being informative about the node's…

统计方法学 · 统计学 2025-01-07 Edward McFowland , Cosma Rohilla Shalizi

Researchers have focused on understanding how individual's behavior is influenced by the behaviors of their peers in observational studies of social networks. Identifying and estimating causal peer influence, however, is challenging due to…

应用统计 · 统计学 2024-06-18 Seungha Um , Tracy Sweet , Samrachana Adhikari

We address the problem of using observational data to estimate peer contagion effects, the influence of treatments applied to individuals in a network on the outcomes of their neighbors. A main challenge to such estimation is that homophily…

社会与信息网络 · 计算机科学 2022-05-18 Irina Cristali , Victor Veitch

Contagion effect refers to the causal effect of peers' behavior on the outcome of an individual in social networks. Contagion can be confounded due to latent homophily which makes contagion effect estimation very hard: nodes in a homophilic…

机器学习 · 计算机科学 2023-10-19 Zahra Fatemi , Elena Zheleva

We investigate peer role model influence on successful graduation from Therapeutic Communities (TCs) for substance abuse and criminal behavior. We use data from 3 TCs that kept records of exchanges of affirmations among residents and their…

统计方法学 · 统计学 2024-06-11 Shanjukta Nath , Keith Warren , Subhadeep Paul

An increasing number of scholars are using longitudinal social network data to try to obtain estimates of peer or social influence effects. These data may provide additional statistical leverage, but they can introduce new inferential…

应用统计 · 统计学 2011-06-20 Hans Noel , Brendan Nyhan

A prominent threat to causal inference about peer effects over social networks is the presence of homophily bias, that is, social influence between friends and families is entangled with common characteristics or underlying similarities…

统计方法学 · 统计学 2020-02-18 Lan Liu , Eric Tchetgen Tchetgen

We examine how three different communication processes operating through social networks are affected by homophily -- the tendency of individuals to associate with others similar to themselves. Homophily has no effect if messages are…

物理与社会 · 物理学 2009-09-29 Benjamin Golub , Matthew O. Jackson

I study peer effects that arise from irreversible decisions in the absence of a standard social equilibrium. I model a latent sequence of decisions in continuous time and obtain a closed-form expression for the likelihood, which allows to…

计量经济学 · 经济学 2026-02-18 Vincent Starck

Understanding susceptibility to online influence is crucial for mitigating the spread of misinformation and protecting vulnerable audiences. This paper investigates susceptibility to influence within social networks, focusing on the…

社会与信息网络 · 计算机科学 2025-05-15 Luca Luceri , Jinyi Ye , Julie Jiang , Emilio Ferrara

As algorithmic tools increasingly aid experts in making consequential decisions, the need to understand the precise factors that mediate their influence has grown commensurately. In this paper, we present a crowdsourcing vignette study…

人机交互 · 计算机科学 2022-05-20 Riccardo Fogliato , Sina Fazelpour , Shantanu Gupta , Zachary Lipton , David Danks

The Linear Threshold Model is a widely used model that describes how information diffuses through a social network. According to this model, an individual adopts an idea or product after the proportion of their neighbors who have adopted it…

社会与信息网络 · 计算机科学 2022-01-28 Christopher Tran , Elena Zheleva

We consider processes on social networks that can potentially involve three factors: homophily, or the formation of social ties due to matching individual traits; social contagion, also known as social influence; and the causal effect of an…

应用统计 · 统计学 2022-03-18 Cosma Rohilla Shalizi , Andrew C. Thomas

Homophily and social influence are two key concepts of social network analysis. Distinguishing between these phenomena is difficult, and approaches to disambiguate the two have been primarily limited to longitudinal data analyses. In this…

统计方法学 · 统计学 2024-05-29 Hanh T. D. Pham , Daniel K. Sewell

We consider a discrete opinion formation problem in a setting where agents are influenced by both information diffused by their social relations and from recommendations received directly from the social media manager. We study how the…

社会与信息网络 · 计算机科学 2022-04-28 Vincenzo Auletta , Antonio Coppola , Diodato Ferraioli

It is widely believed that one's peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the…

社会与信息网络 · 计算机科学 2020-09-09 Soumajyoti Sarkar , Ashkan Aleali , Paulo Shakarian , Mika Armenta , Danielle Sanchez , Kiran Lakkaraju

Subscriber churn remains a top challenge for wireless carriers. These carriers need to understand the determinants of churn to confidently apply effective retention strategies to ensure their profitability and growth. In this paper, we look…

社会与信息网络 · 计算机科学 2016-01-28 Qiwei Han , Pedro Ferreira

We develop a general model of discrete choice that incorporates peer effects in preferences and consideration sets. We characterize the equilibrium behavior and establish conditions under which all parts of the model can be recovered from a…

综合经济学 · 经济学 2026-02-05 Nail Kashaev , Natalia Lazzati , Ruli Xiao

How social networks influence human behavior has been an interesting topic in applied research. Existing methods often utilized scale-level behavioral data to estimate the influence of a social network on human behavior. This study proposes…

社会与信息网络 · 计算机科学 2025-01-08 Jina Park , Ick Hoon Jin , Minjeong Jeon

Many online social networks thrive on automatic sharing of friends' activities to a user through activity feeds, which may influence the user's next actions. However, identifying such social influence is tricky because these activities are…

社会与信息网络 · 计算机科学 2016-04-06 Amit Sharma , Dan Cosley
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