59 research outputs found
Homophily and Contagion Are Generically Confounded in Observational Social Network Studies
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 individual's covariates on their behavior or other measurable responses.
We show that, generically, all of these are confounded with each other.
Distinguishing them from one another requires strong assumptions on the
parametrization of the social process or on the adequacy of the covariates used
(or both). In particular we demonstrate, with simple examples, that asymmetries
in regression coefficients cannot identify causal effects, and that very simple
models of imitation (a form of social contagion) can produce substantial
correlations between an individual's enduring traits and their choices, even
when there is no intrinsic affinity between them. We also suggest some possible
constructive responses to these results.Comment: 27 pages, 9 figures. V2: Revised in response to referees. V3: Ditt
Social Algorithms
This article concerns the review of a special class of swarm intelligence
based algorithms for solving optimization problems and these algorithms can be
referred to as social algorithms. Social algorithms use multiple agents and the
social interactions to design rules for algorithms so as to mimic certain
successful characteristics of the social/biological systems such as ants, bees,
bats, birds and animals.Comment: Encyclopedia of Complexity and Systems Science, 201
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