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Number-of-Cited-References = {{58}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{1}},
Usage-Count-Since-2013 = {{23}},
Journal-ISO = {{Soc. Networks}},
Doc-Delivery-Number = {{067OD}},
Unique-ID = {{ISI:000313304100021}},
}

@incollection{ ISI:000339965700013,
Author = {Smith, Jeffrey A.},
Editor = {{Liao, TF}},
Title = {{Macrostructure from Microstructure: Generating Whole Systems from Ego
   Networks}},
Booktitle = {{SOCIOLOGICAL METHODOLOGY 2012, VOL 42}},
Series = {{Sociological Methodology}},
Year = {{2012}},
Volume = {{42}},
Pages = {{155-205}},
Abstract = {{This article presents a new simulation method to make global network
   inference from sampled data. The proposed method takes sampled ego
   network data and uses exponential random graph models (ERGM) to
   reconstruct the features of the true, unknown network. After describing
   the method, the author presents two validity checks of the approach: the
   first uses the 20 largest Add Health networks while the second uses the
   Sociology Coauthorship network in the 1990s. For each test, I take
   random ego network samples from the known networks and use my method to
   make global network inference. The method successfully reproduces the
   properties of the networks, such as distance and main component size.
   The results also suggest that simpler, baseline models provide
   considerably worse estimates for most network properties. The paper
   concludes with a discussion of the bounds/limitations of ego network
   sampling as well as possible extensions to the proposed approach.}},
Publisher = {{SAGE PUBLICATIONS INC}},
Address = {{2455 TELLER RD, NEWBURY PK, CA 91320 USA}},
Type = {{Article; Book Chapter}},
Language = {{English}},
Affiliation = {{Smith, JA (Reprint Author), Duke Sociol, 268 Soc Psych Bldg,Box 90088, Durham, NC 27708 USA.
   Smith, Jeffrey A., Duke Univ, Durham, NC 27706 USA.}},
DOI = {{10.1177/0081175012455628}},
ISSN = {{0081-1750}},
ISBN = {{978-1-4522-8246-6}},
Keywords = {{Networks; sampling; simulation; ERGM}},
Keywords-Plus = {{EXPONENTIAL FAMILY MODELS; RANDOM GRAPH MODELS; SOCIAL NETWORKS;
   PERSONAL NETWORKS; NAME GENERATOR; MARKOV GRAPHS; 1ST STEPS; SNOWBALL;
   CENTRALITY; COHESION}},
Research-Areas = {{Mathematical Methods In Social Sciences; Sociology}},
Web-of-Science-Categories  = {{Social Sciences, Mathematical Methods; Sociology}},
Author-Email = {{jas76@soc.duke.edu}},
Funding-Acknowledgement = {{NICHD NIH HHS {[}R21 HD068317, P01 HD031921]}},
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Number-of-Cited-References = {{73}},
Times-Cited = {{11}},
Usage-Count-(Last-180-days) = {{2}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Sociol. Methodol.}},
Doc-Delivery-Number = {{BA9YK}},
Unique-ID = {{ISI:000339965700013}},
}

@article{ ISI:000260739200002,
Author = {Lopez-Pintado, Dunia and Watts, Duncan J.},
Title = {{SOCIAL INFLUENCE, BINARY DECISIONS AND COLLECTIVE DYNAMICS}},
Journal = {{RATIONALITY AND SOCIETY}},
Year = {{2008}},
Volume = {{20}},
Number = {{4}},
Pages = {{399-443}},
Month = {{NOV}},
Abstract = {{In this paper we address the general question of how social influence
   determines collective outcomes for large populations of individuals
   faced with binary decisions. First, we define conditions under which the
   behavior of individuals making binary decisions can be described in
   terms of what we call an influence-response function: a one-dimensional
   function of the (weighted) number of individuals choosing each of the
   alternatives. And second, we demonstrate that, under the assumptions of
   global and anonymous interactions, general knowledge of the
   influence-response functions is sufficient to compute equilibrium, and
   even non-equilibrium, properties of the collective dynamics. By enabling
   us to treat in a consistent manner classes of decisions that have
   previously been analyzed separately, our framework allows us to find
   similarities between apparently quite different kinds of decision
   situations, and conversely to identify important differences between
   decisions that would otherwise appear very similar.}},
Publisher = {{SAGE PUBLICATIONS LTD}},
Address = {{1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Lopez-Pintado, D (Reprint Author), Univ Pablo Olavide, Dept Econ, Carretera Utrera Km 1, Seville 41013, Spain.
   Lopez-Pintado, Dunia; Watts, Duncan J., Univ Pablo Olavide, Dept Econ, Seville 41013, Spain.}},
DOI = {{10.1177/1043463108096787}},
ISSN = {{1043-4631}},
Keywords = {{social influence; influence-response function; collective outcomes;
   best-response dynamics}},
Keywords-Plus = {{INFORMATIONAL CASCADES; THRESHOLD MODELS; ANTI-COORDINATION; NETWORK
   FORMATION; CRITICAL MASS; DIFFUSION; BEHAVIOR; GAMES; CONFORMITY;
   CONTAGION}},
Research-Areas = {{Sociology}},
Web-of-Science-Categories  = {{Sociology}},
Author-Email = {{dlopez@upo.es}},
ResearcherID-Numbers = {{Watts, Duncan/J-6483-2012}},
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Journal-ISO = {{Ration. Soc.}},
Doc-Delivery-Number = {{370CB}},
Unique-ID = {{ISI:000260739200002}},
}

@incollection{ ISI:000288018200016,
Author = {Jackson, MO},
Title = {{Social and Economic Networks}},
Booktitle = {{SOCIAL AND ECONOMIC NETWORKS}},
Year = {{2008}},
Pages = {{1-504}},
Publisher = {{PRINCETON UNIV PRESS}},
Address = {{41 WILLIAM ST, PRINCETON, NJ 08540 USA}},
Type = {{Book}},
Language = {{English}},
ISBN = {{978-0-691-13440-6}},
Keywords-Plus = {{SMALL-WORLD NETWORK; RISK-SHARING NETWORKS; SCALE-FREE NETWORKS;
   OF-MOUTH COMMUNICATION; RANDOM GRAPHS; COMPLEX NETWORKS; LABOR-MARKET;
   WEAK-TIES; STRATEGIC COMPLEMENTARITIES; COALITION-FORMATION}},
Research-Areas = {{Business \& Economics; Sociology}},
Web-of-Science-Categories  = {{Economics; Sociology}},
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