# Bayesian Analysis of Social Influence

arXiv: https://arxiv.org/abs/2006.16464 · HTML: https://mlsanity.com/paper/2006.16464/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 30 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [Modeling the Social Influence of COVID-19 via Personalized Propagation with Deep Learning](https://mlsanity.com/paper/2207.13016/) (2022)

## Abstract (arXiv)

The network influence model is a model for binary outcome variables that accounts for dependencies between outcomes for units that are relationally tied. The basic influence model was previously extended to afford a suite of new dependence assumptions and because of its relation to traditional Markov random field models it is often referred to as the auto logistic actor-attribute model (ALAAM). We extend on current approaches for fitting ALAAMs by presenting a comprehensive Bayesian inference scheme that supports testing of dependencies across subsets of data and the presence of missing data. We illustrate different aspects of the procedures through three empirical examples: masculinity attitudes in an all-male Australian school class, educational progression in Swedish schools, and un-employment among adults in a community sample in Australia.