Refining the Semantics of Social Influence

TL;DR

This paper examines how different definitions of extended social neighborhoods influence the understanding of peer effects and influence modeling on networks, highlighting the importance of semantic clarity.

Contribution

It identifies ambiguity in defining extended neighborhoods in social influence analysis and quantifies how different semantics impact model selection through experiments.

Findings

Different semantics lead to varying sets of extended neighbors.

The choice of semantics significantly affects influence model outcomes.

Experimental results on synthetic and real networks demonstrate these effects.

Abstract

With the proliferation of network data, researchers are increasingly focusing on questions investigating phenomena occurring on networks. This often includes analysis of peer-effects, i.e., how the connections of an individual affect that individual's behavior. This type of influence is not limited to direct connections of an individual (such as friends), but also to individuals that are connected through longer paths (for example, friends of friends, or friends of friends of friends). In this work, we identify an ambiguity in the definition of what constitutes the extended neighborhood of an individual. This ambiguity gives rise to different semantics and supports different types of underlying phenomena. We present experimental results, both on synthetic and real networks, that quantify differences among the sets of extended neighbors under different semantics. Finally, we provide experimental evidence that demonstrates how the use of different semantics affects model selection.