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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…

Methodology · Statistics 2025-01-07 Edward McFowland , Cosma Rohilla Shalizi

We study network games in which players choose both the partners with whom they associate and an action level (e.g., effort) that creates spillovers for those partners. We introduce a framework and two solution concepts, extending standard…

Theoretical Economics · Economics 2024-02-07 Evan Sadler , Benjamin Golub

Social network interference induces complex dependencies where a unit's outcome is influenced not only by its own exposure and mediator but also by those of connected neighbors. In such settings, a significant challenge lies in…

Methodology · Statistics 2026-03-03 Ritoban Kundu , Peter X. K. Song

Estimating causal effects on networks is challenging because treatments may affect both treated units and their neighbors, while network homophily induces dependence and confounding. These challenges are amplified when causal effects are…

Machine Learning · Statistics 2026-05-12 Yuanchen Wu , Yubai Yuan

In the linear-in-means model, endogeneity arises naturally due to the reflection problem. A common solution is to use Instrumental Variables (IVs) based on higher-order network links, such as using friends-of-friends' characteristics. We…

Econometrics · Economics 2026-03-02 Nathan Canen , Shantanu Chadha

Peer effects, in which the behavior of an individual is affected by the behavior of their peers, are posited by multiple theories in the social sciences. Other processes can also produce behaviors that are correlated in networks and groups,…

Methodology · Statistics 2021-02-16 Dean Eckles , Eytan Bakshy

This paper develops a general framework for identifying causal effects in settings with spillovers, where both outcomes and endogenous treatment decisions are influenced by peers within a known group. It introduces the generalized local…

Econometrics · Economics 2025-12-01 Huan Wu

Claiming causal inferences in network settings necessitates careful consideration of the often complex dependency between outcomes for actors. Of particular importance are treatment spillover or outcome interference effects. We consider…

Methodology · Statistics 2022-07-18 Duncan A. Clark , Mark S. Handcock

This article develops a class of models called Sender/Receiver Finite Mixture Exponential Random Graph Models (SRFM-ERGMs) that enables inference on networks. This class of models extends the existing Exponential Random Graph Modeling…

Methodology · Statistics 2019-09-06 Teague R Henry , Kathleen M Gates , Mitchell J Prinstein , Douglas Steinley

We present a stochastic imitation-based model of opinion dynamics in which agents balance social conformity with responsiveness to an external signal. The model captures how populations evolve between two binary opinion states, driven by…

Physics and Society · Physics 2025-08-12 Federica De Domenico , Fabio Caccioli , Giacomo Livan

When opinion spread is studied, peer pressure is often modeled by interactions of more than two individuals (higher-order interactions). In our work, we introduce a two-layer random hypergraph model, in which hyperedges represent households…

Social and Information Networks · Computer Science 2025-12-30 Ágnes Backhausz , Villő Csiszár , Balázs Csegő Kolok , Damján Tárkányi , András Zempléni

This paper develops a continuous functional framework for treatment effects propagating through geographic space and economic networks. We derive a master equation from three independent economic foundations -- heterogeneous agent…

Econometrics · Economics 2025-12-29 Tatsuru Kikuchi

The global dynamics of event cascades are often governed by the local dynamics of peer influence. However, detecting social influence from observational data is challenging due to confounds like homophily and practical issues like missing…

Social and Information Networks · Computer Science 2019-07-22 Sandeep Soni , Shawn Ling Ramirez , Jacob Eisenstein

Homophily based on observables is widespread in networks. Therefore, homophily based on unobservables (fixed effects) is also likely to be an important determinant of the interaction outcomes. Failing to properly account for latent…

Econometrics · Economics 2026-02-09 Andrei Zeleneev

Practitioners in medicine, business, political science, and other fields are increasingly aware that decisions should be personalized to each patient, customer, or voter. A given treatment (e.g. a drug or advertisement) should be…

Machine Learning · Statistics 2018-06-15 Alejandro Schuler , Michael Baiocchi , Robert Tibshirani , Nigam Shah

In recent years networks have gained unprecedented attention in studying a broad range of topics, among them in complex systems research. In particular, multi-agent systems have seen an increased recognition of the importance of the…

Physics and Society · Physics 2007-05-23 László Gulyás , Elenna R. Dugundji

We propose an Embedding Network Autoregressive Model for multivariate networked longitudinal data. We assume the network is generated from a latent variable model, and these unobserved variables are included in a structural peer effect…

Methodology · Statistics 2025-03-25 Jae Ho Chang , Subhadeep Paul

Many societal challenges, such as climate change or disease outbreaks, require coordinated behavioral changes. For many behaviors, the tendency of individuals to adhere to social norms can reinforce the status quo. However, these same…

Many-to-one matching markets exist in numerous different forms, such as college admissions, matching medical interns to hospitals for residencies, assigning housing to college students, and the classic firms and workers market. In all these…

Social and Information Networks · Computer Science 2011-07-25 Elizabeth Bodine-Baron , Christina Lee , Anthony Chong , Babak Hassibi , Adam Wierman

This paper investigates causal influences between agents linked by a social graph and interacting over time. In particular, the work examines the dynamics of social learning models and distributed decision-making protocols, and derives…

Social and Information Networks · Computer Science 2026-05-19 Mert Kayaalp , Ali H. Sayed