text:
@incollection{ ISI:000387351800011,
Author = {Dickison, ME and Magnani, M and Rossi, L},
Title = {{Multilayer Social Networks}},
Booktitle = {{MULTILAYER SOCIAL NETWORKS}},
Year = {{2016}},
Pages = {{1-203}},
Publisher = {{CAMBRIDGE UNIV PRESS}},
Address = {{THE PITT BUILDING, TRUMPINGTON ST, CAMBRIDGE CB2 1RP, CAMBS, ENGLAND}},
Type = {{Book}},
Language = {{English}},
DOI = {{10.1017/CBO9781139941907}},
ISBN = {{978-1-107-43875-0; 978-1-107-07949-6}},
Keywords-Plus = {{RANDOM GRAPH MODELS; SMALL-WORLD NETWORKS; MULTIPLEX NETWORKS;
   INTERDEPENDENT NETWORKS; COMMUNITY DETECTION; MULTIDIMENSIONAL NETWORKS;
   MULTILEVEL NETWORKS; SOCIOLOGICAL FORM; INFORMATION-FLOW; VISUAL
   ANALYTICS}},
Research-Areas = {{Computer Science; Communication; Psychology; Sociology}},
Web-of-Science-Categories  = {{Computer Science, Information Systems; Communication; Psychology,
   Social; Sociology}},
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Times-Cited = {{1}},
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Doc-Delivery-Number = {{BG2HD}},
Unique-ID = {{ISI:000387351800011}},
}

@article{ ISI:000352892200004,
Author = {Smith, Jeffrey A.},
Title = {{Global Network Inference from Ego Network Samples: Testing a Simulation
   Approach}},
Journal = {{JOURNAL OF MATHEMATICAL SOCIOLOGY}},
Year = {{2015}},
Volume = {{39}},
Number = {{2}},
Pages = {{125-162}},
Month = {{APR 3}},
Abstract = {{Network sampling poses a radical idea: that it is possible to measure
   global network structure without the full population coverage assumed in
   most network studies. Network sampling is only useful, however, if a
   researcher can produce accurate global network estimates. This article
   explores the practicality of making network inference, focusing on the
   approach introduced in Smith (2012). The method uses sampled ego network
   data and simulation techniques to make inference about the global
   features of the true, unknown network. The validity check here includes
   more difficult scenarios than previous tests, including those that go
   beyond the initial scope conditions of the method. I examine networks
   with a skewed degree distribution and surveys that limit the number of
   social ties a respondent can list. For each network/survey combination,
   I take a random ego network sample, run the simulation method, and
   compare the results to the true values (using measures of connectivity
   and cohesion). I also test the method on local measures of network
   structure. The results, on the whole, are encouraging. The method
   produces good estimates even in cases where the degree distribution is
   skewed and the survey is strongly restricted. I also find that is it
   better to not truncate the survey if possible. If the survey must be
   restricted, the researcher would do well to infer the missing data,
   rather than use the raw data naively.}},
Publisher = {{TAYLOR \& FRANCIS INC}},
Address = {{530 WALNUT STREET, STE 850, PHILADELPHIA, PA 19106 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Smith, JA (Reprint Author), Univ Nebraska, Dept Sociol, 711 Oldfather Hall, Lincoln, NE 68588 USA.
   Smith, Jeffrey A., Univ Nebraska, Dept Sociol, Lincoln, NE 68588 USA.}},
DOI = {{10.1080/0022250X.2014.994621}},
ISSN = {{0022-250X}},
EISSN = {{1545-5874}},
Keywords = {{social networks; exponential random graph model (ERGM); simulation}},
Keywords-Plus = {{RANDOM GRAPH MODELS; SOCIAL NETWORKS; NAME GENERATOR; UNITED-STATES;
   MARKOV GRAPHS; RACE; FRIENDSHIP; DISTANCE; TIES; SEX}},
Research-Areas = {{Mathematics; Mathematical Methods In Social Sciences; Sociology}},
Web-of-Science-Categories  = {{Mathematics, Interdisciplinary Applications; Social Sciences,
   Mathematical Methods; Sociology}},
Author-Email = {{jsmith77@unl.edu}},
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Number-of-Cited-References = {{68}},
Times-Cited = {{1}},
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Journal-ISO = {{J. Math. Sociol.}},
Doc-Delivery-Number = {{CF9NQ}},
Unique-ID = {{ISI:000352892200004}},
}

@article{ ISI:000355348100001,
Author = {Centola, Damon},
Title = {{The Social Origins of Networks and Diffusion}},
Journal = {{AMERICAN JOURNAL OF SOCIOLOGY}},
Year = {{2015}},
Volume = {{120}},
Number = {{5}},
Pages = {{1295-1338}},
Month = {{MAR}},
Abstract = {{Recent research on social contagion has demonstrated significant effects
   of network topology on the dynamics of diffusion. However, network
   topologies are not given a priori. Rather, they are patterns of
   relations that emerge from individual and structural features of
   society, such as population composition, group heterogeneity, homophily,
   and social consolidation. Following Blau and Schwartz, the author
   develops a model of social network formation that explores how social
   and structural constraints on tie formation generate emergent social
   topologies and then explores the effectiveness of these social networks
   for the dynamics of social diffusion. Results show that, at one extreme,
   high levels of consolidation can create highly balkanized communities
   with poor integration of shared norms and practices. As suggested by
   Blau and Schwartz, reducing consolidation creates more crosscutting
   circles and significantly improves the dynamics of social diffusion
   across the population. However, the author finds that further reducing
   consolidation creates highly intersecting social networks that fail to
   support the widespread diffusion of norms and practices, indicating that
   successful social diffusion can depend on moderate to high levels of
   structural consolidation.}},
Publisher = {{UNIV CHICAGO PRESS}},
Address = {{1427 E 60TH ST, CHICAGO, IL 60637-2954 USA}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Centola, D (Reprint Author), Univ Penn, Annenberg Sch Commun, 3620 Walnut St, Philadelphia, PA 19104 USA.
   Univ Penn, Annenberg Sch Commun, Philadelphia, PA 19104 USA.}},
DOI = {{10.1086/681275}},
ISSN = {{0002-9602}},
EISSN = {{1537-5390}},
Keywords-Plus = {{SMALL-WORLD; DYNAMICS; BEHAVIOR; MODELS; TIES; HETEROGENEITY;
   FRIENDSHIP; STRENGTH; IDENTITY; CULTURE}},
Research-Areas = {{Sociology}},
Web-of-Science-Categories  = {{Sociology}},
Author-Email = {{dcentola@asc.upenn.edu}},
Funding-Acknowledgement = {{James S. McDonnell Foundation}},
Funding-Text = {{The author gratefully acknowledges suggestions and guidance from Duncan
   Watts during the early stages of this project and extensive comments
   from Paul DiMaggio, Arnout van de Rijt, Peter Dodds, Michael Macy, Ezra
   Zuckerman, Ray Reagans, and Ronald Burt. This research was supported in
   part by the James S. McDonnell Foundation through a Studying Complex
   Systems grant to the author.}},
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Journal-ISO = {{Am. J. Sociol.}},
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Unique-ID = {{ISI:000355348100001}},
}

@incollection{ ISI:000359855300004,
Author = {Centeno, Miguel A. and Nag, Manish and Patterson, Thayer S. and Shaver,
   Andrew and Windawi, A. Jason},
Editor = {{Cook, KS and Massey, DS}},
Title = {{The Emergence of Global Systemic Risk}},
Booktitle = {{ANNUAL REVIEW OF SOCIOLOGY, VOL 41}},
Series = {{Annual Review of Sociology}},
Year = {{2015}},
Volume = {{41}},
Pages = {{65-85}},
Abstract = {{In this article, we discuss the increasing interdependence of societies,
   focusing specifically on issues of systemic instability and fragility
   generated by the new and unprecedented level of connectedness and
   complexity resulting from globalization. We define the global system as
   a set of tightly coupled interactions that allow for the continued flow
   of information, capital, goods, services, and people. Using the general
   concepts of globality, complexity, networks, and the nature of risk, we
   analyze case studies of trade, finance, infrastructure, climate change,
   and public health to develop empirical support for the concept of global
   systemic risk. We seek to identify and describe the sources and nature
   of such risks and methods of thinking about risks that may inform future
   academic research and policy-making decisions.}},
Publisher = {{ANNUAL REVIEWS}},
Address = {{4139 EL CAMINO WAY, PO BOX 10139, PALO ALTO, CA 94303-0897 USA}},
Type = {{Article; Book Chapter}},
Language = {{English}},
Affiliation = {{Centeno, MA (Reprint Author), Princeton Univ, Dept Sociol, Princeton, NJ 08544 USA.
   Centeno, Miguel A.; Nag, Manish; Windawi, A. Jason, Princeton Univ, Dept Sociol, Princeton, NJ 08544 USA.
   Patterson, Thayer S., Princeton Univ, PIIRS Global System Risk Res Commun, Princeton, NJ 08544 USA.
   Shaver, Andrew, Princeton Univ, Woodrow Wilson Sch, Princeton, NJ 08544 USA.}},
DOI = {{10.1146/annurev-soc-073014-112317}},
ISSN = {{0360-0572}},
ISBN = {{978-0-8243-2241-0}},
Keywords = {{complexity; emergence; risk; globality; networks}},
Keywords-Plus = {{INTERNATIONAL-TRADE; INFECTIOUS-DISEASES; NETWORK ANALYSIS;
   CLIMATE-CHANGE; INTERDEPENDENT NETWORKS; CRITICAL TRANSITIONS; FINANCIAL
   CONTAGION; GREEN-REVOLUTION; COMPLEX NETWORKS; GLASS-STEAGALL}},
Research-Areas = {{Sociology}},
Web-of-Science-Categories  = {{Sociology}},
Author-Email = {{cenmiga@princeton.edu
   mnag@princeton.edu
   tspatter@princeton.edu
   ashaver@princeton.edu
   awindawi@princeton.edu}},
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Number-of-Cited-References = {{183}},
Times-Cited = {{1}},
Usage-Count-(Last-180-days) = {{6}},
Usage-Count-Since-2013 = {{26}},
Journal-ISO = {{Annu. Rev. Sociol.}},
Doc-Delivery-Number = {{BD3LG}},
Unique-ID = {{ISI:000359855300004}},
}

@article{ ISI:000340338600001,
Author = {Morales, A. J. and Borondo, J. and Losada, J. C. and Benito, R. M.},
Title = {{Efficiency of human activity on information spreading on Twitter}},
Journal = {{SOCIAL NETWORKS}},
Year = {{2014}},
Volume = {{39}},
Pages = {{1-11}},
Month = {{OCT}},
Abstract = {{Understanding the collective reaction to individual actions is key to
   effectively spread information in social media. In this work we define
   efficiency on Twitter, as the ratio between the emergent spreading
   process and the activity employed by the user. We characterize this
   property by means of a quantitative analysis of the structural and
   dynamical patterns emergent from human interactions, and show it to be
   universal across several Twitter conversations. We found that some
   influential users efficiently cause remarkable collective reactions by
   each message sent, while the majority of users must employ extremely
   larger efforts to reach similar effects. Next we propose a model that
   reproduces the retweet cascades occurring on Twitter to explain the
   emergent distribution of the user efficiency. The model shows that the
   dynamical patterns of the conversations are strongly conditioned by the
   topology of the underlying network. We conclude that the appearance of a
   small fraction of extremely efficient users results from the
   heterogeneity of the followers network and independently of the
   individual user behavior. (C) 2014 Elsevier B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Benito, RM (Reprint Author), Univ Politecn Madrid, ETSI Agronomos, Grp Sistemas Complejos, Dept Fis \& Mecan, E-28040 Madrid, Spain.
   Morales, A. J.; Borondo, J.; Losada, J. C.; Benito, R. M., Univ Politecn Madrid, ETSI Agronomos, Grp Sistemas Complejos, Dept Fis \& Mecan, E-28040 Madrid, Spain.}},
DOI = {{10.1016/j.socnet.2014.03.007}},
ISSN = {{0378-8733}},
EISSN = {{1879-2111}},
Keywords = {{Complex networks; Social networks analysis; Information spreading; User
   behavior; Twitter; Influence}},
Keywords-Plus = {{SOCIAL NETWORK; MODEL}},
Research-Areas = {{Anthropology; Sociology}},
Web-of-Science-Categories  = {{Anthropology; Sociology}},
Author-Email = {{rosamaria.benito@upm.es}},
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Number-of-Cited-References = {{35}},
Times-Cited = {{10}},
Usage-Count-(Last-180-days) = {{6}},
Usage-Count-Since-2013 = {{62}},
Journal-ISO = {{Soc. Networks}},
Doc-Delivery-Number = {{AN1JM}},
Unique-ID = {{ISI:000340338600001}},
}

@article{ ISI:000319679200002,
Author = {Corten, Rense and Knecht, Andrea},
Title = {{Alcohol use among adolescents as a coordination problem in a dynamic
   network}},
Journal = {{RATIONALITY AND SOCIETY}},
Year = {{2013}},
Volume = {{25}},
Number = {{2}},
Pages = {{146-177}},
Month = {{MAY}},
Abstract = {{Whereas most research on substance (ab)use by adolescents studies only
   the effects of personal networks of adolescents, we propose a
   theoretical approach that allows for predictions on the effects of the
   macro-level social network structure on usage rates. We model alcohol
   use as risk-dominant but inefficient behaviour in a coordination
   problem, given that adolescents face incentives to align their behaviour
   with their friends. We propose a game-theoretical model in which actors
   choose behaviour in a repeated coordination game in an endogenous
   network. Predictions on levels of alcohol use depending on initial
   network structure are based on computer simulations of this model. We
   test the predictions using longitudinal data on alcohol use and
   friendship choices in school classes in Dutch high schools. We replicate
   the predicted `catalysing' effect of initial network density on the
   development of alcohol use but the predicted opposing effect of
   centralization could not be confirmed.}},
Publisher = {{SAGE PUBLICATIONS LTD}},
Address = {{1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Corten, R (Reprint Author), Tilburg Univ, Sch Social \& Behav Sci, Dept Sociol, POB 90153, NL-5000 LE Tilburg, Netherlands.
   Corten, Rense, Tilburg Univ, NL-5000 LE Tilburg, Netherlands.
   Knecht, Andrea, Univ Erlangen Nurnberg, Erlangen, Germany.}},
DOI = {{10.1177/1043463112473793}},
ISSN = {{1043-4631}},
EISSN = {{1461-7358}},
Keywords = {{Adolescents; game theory; simulation; social networks; substance abuse}},
Keywords-Plus = {{LARGE SOCIAL NETWORK; SUBSTANCE USE; PEER INFLUENCE; DRUG-USE; BEHAVIOR;
   FRIENDSHIP; SPREAD; TIES; COEVOLUTION; CIGARETTE}},
Research-Areas = {{Sociology}},
Web-of-Science-Categories  = {{Sociology}},
Author-Email = {{r.corten@uvt.nl}},
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Number-of-Cited-References = {{53}},
Times-Cited = {{4}},
Usage-Count-(Last-180-days) = {{0}},
Usage-Count-Since-2013 = {{12}},
Journal-ISO = {{Ration. Soc.}},
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}

@article{ ISI:000313304100021,
Author = {Flores, Ramon and Koster, Maurice and Lindner, Ines and Molina, Elisenda},
Title = {{Networks and collective action}},
Journal = {{SOCIAL NETWORKS}},
Year = {{2012}},
Volume = {{34}},
Number = {{4}},
Pages = {{570-584}},
Month = {{OCT}},
Abstract = {{This paper proposes a new measure for a group's ability to lead society
   to adopt their standard of behavior, which in particular takes account
   of the time the group takes to convince the whole society to adopt their
   position. This notion of a group's power to initiate action is computed
   as the reciprocal of the resistance against it, which is in turn given
   by the expected absorption time of a related finite state partial Markov
   chain that captures the social dynamics. The measure is applicable and
   meaningful in a variety of models where interaction between agents is
   formalized through (weighted) binary relations. Using Percolation
   Theory, it is shown that the group power is monotonic as a function of
   groups of agents. We also explain the differences between our measure
   and those discussed in the literature on Graph Theory, and illustrate
   all these concerns by a thorough analysis of two particular cases: the
   Wolfe Primate Data and the 11S hijackers' network. (C) 2012 Elsevier
   B.V. All rights reserved.}},
Publisher = {{ELSEVIER SCIENCE BV}},
Address = {{PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS}},
Type = {{Article}},
Language = {{English}},
Affiliation = {{Molina, E (Reprint Author), Univ Carlos III Madrid, Dept Stat, E-28903 Getafe, Spain.
   Flores, Ramon; Molina, Elisenda, Univ Carlos III Madrid, Dept Stat, E-28903 Getafe, Spain.
   Koster, Maurice, Univ Amsterdam, Amsterdam Sch Econ, NL-1012 WX Amsterdam, Netherlands.
   Lindner, Ines, Vrije Univ Amsterdam, Dept Econometr \& Operat Res, Amsterdam, Netherlands.}},
DOI = {{10.1016/j.socnet.2012.06.003}},
ISSN = {{0378-8733}},
Keywords = {{Collective action; Social networks; Influence and diffusion models;
   Network intervention; Group centrality measures}},
Keywords-Plus = {{SOCIAL-INFLUENCE; CENTRALITY; MODEL; DIFFUSION; CONSENSUS; CONTAGION;
   CASCADES; THEOREMS; BEHAVIOR; SYSTEMS}},
Research-Areas = {{Anthropology; Sociology}},
Web-of-Science-Categories  = {{Anthropology; Sociology}},
Author-Email = {{ramonjesus.flores@uc3m.es
   M.A.L.Koster@uva.nl
   ilindner@feweb.vu.nl
   elisenda.molina@uc3m.es}},
ResearcherID-Numbers = {{Molina, Elisenda/C-3938-2011
   Lindner, Ines/C-8728-2014
   Flores, Ramon/I-3135-2015
   }},
ORCID-Numbers = {{Molina, Elisenda/0000-0002-5072-6550
   MOLINA, ELISENDA/0000-0002-9458-323X}},
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