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Alters as species Predicting personal network size from contact diaries.pdf
Social Networks 45 (2016) 78–88
Contents lists available at ScienceDirect
Social Networks
journal homepage: /locate/socnet
Alters as species: Predicting personal network size from contact diaries
Tso-Jung Yen a,?, Yang-chih Fu b, Jing-Shiang Hwang a
a Institute of Statistical Science, Academia Sinica, Taiwan b Institute of Sociology, Academia Sinica, Taiwan
article info
Article history: Available online 7 January 2016
Keywords: Personal networks Ego and alters Contact diaries Alter accumulation curves Mixture of Dirichlet processes
abstract
Like wildlife species in an ecological system, members within a personal network (or alters) constantly
shift and often remain hard to count. Previous studies often estimated the size of such personal networks
using information given by a focal person (or ego), who names a list of friends and acquaintances, or
someone known or related, that meet certain speci?ed criteria. In a search for alternative methods, we
estimate the number of alters using contact diaries that help reveal active and comprehensive interac-
tions, which enable us to predict personal network size from a longitudinal perspective. By exploring
contact frequencies between ego and alters, we propose a modeling approach based on species accu-
mulation curves from ecology. Under this approach, the contact frequency between ego and alter often
turns out to be a mixture of binomial distributions, and the number of alters with whom ego may make
contact in the future is assumed to follow a speci?ed discrete distribution. We estimate the model with
the Bayesian nonparametric method, in which the distribution of contact probabilities is assumed to be
a mixture of Dirichlet processes. We then demonstrate this approach with a data set containing 48 con-
tact diaries collected over three months and discuss how such an ecological analogy may enrich social
network studies.
? 2015 Elsevier B.V. All rights reserved.
1. Introduction
As important as estimating the population size
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