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  • 1
    UID:
    almafu_9959238876702883
    Format: 1 online resource (xxii, 336 pages) : , digital, PDF file(s).
    Edition: 1st ed.
    ISBN: 1-107-23276-7 , 1-139-85341-4 , 1-107-25326-8 , 1-139-83958-6 , 1-139-84432-6 , 0-511-89470-8 , 1-139-84196-3 , 1-283-83596-7 , 1-139-84077-0
    Series Statement: Structural analysis in the social sciences ; 35
    Content: Exponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide a self-contained, exhaustive account of the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGMs. The authors supply the reader with sufficient detail to specify ERGMs, fit them to data with any of the available software packages and interpret the results.
    Note: Title from publisher's bibliographic system (viewed on 05 Oct 2015). , Machine generated contents note: Introduction Dean Lusher, Johan Koskinen and Garry Robins; 1. What are exponential random graph models Garry Robins and Dean Lusher; 2. The formation of social network structure Dean Lusher and Garry Robins; 3. A simplified account of ERGM as a statistical model Garry Robins and Dean Lusher; 4. An example of ERGM analysis Dean Lusher and Garry Robins; 5. Exponential random graph model fundamentals Johan Koskinene and Galina Daragonova; 6. Dependence graphs and sufficient statistics Johan Koskinen and Galina Daragonova; 7. Social selection, dyadic covariates and geospatial effects Garry Robins and Galina Daragonova; 8. Autologistic actor attribute models Galina Daragonova and Garry Robins; 9. ERGM extensions: models for multiple networks and bipartite networks Peng Wang; 10. Longitudinal models Tom Snijders and Johan Koskinen; 11. Simulation, estimation and goodness of fit Johan Koskinen and Tom Snijders; 12. Illustrations: simulation, estimation and goodness of fit Garry Robins and Dean Lusher; 13. Personal attitudes, perceived attitudes and social structures: a social selection model Dean Lusher and Garry Robins; 14. How to close a hole: exploring alternative closure mechanisms in inter-organizational networks Alessandro Lomi and Francesca Pallotti; 15. Interdependencies between working relations: multivariate ERGMs for advice and satisfaction Yu Zhao and Olaf Rank; 16. Brain, brawn or optimism? The structure and correlates of emergent military leadership Yuval Kalish and Gil Luria; 17. An ALAAM analysis of unemployment: the dual importance of who you know and where you live Galina Daragonova and Philippa Pattison; 18. Longitudinal changes in face-to-face and text message-mediated friendship networks Tasuku Igarashi; 19. The differential impact of directors' social and financial capital on corporate interlock formation Nicholas Harrigan and Matthew Bond; 20. Comparing networks: a structural correspondence between behavioural and recall networks Eric Quintane; 21. Modelling social networks: next steps Philippa Pattison and Tom Snijders. , English
    Additional Edition: ISBN 0-521-19356-7
    Additional Edition: ISBN 0-521-14138-9
    Language: English
    Keywords: Aufsatzsammlung ; Aufsatzsammlung ; Aufsatzsammlung
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Volltext  (lizenzpflichtig)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    kobvindex_GFZ120517
    Format: XXII, 336 S. : graph. Darst.
    ISBN: 9780521141383
    Series Statement: Structural analysis in the social sciences 35
    Content: Contents: Introduction ; 1. What are exponential random graph models ; 2. The formation of social network structure ; 3. A simplified account of ERGM as a statistical model ; 4. An example of ERGM analysis ; 5. Exponential random graph model fundamentals ; 6. Dependence graphs and sufficient statistics ; 7. Social selection, dyadic covariates and geospatial effects ; 8. Autologistic actor attribute models ; 9. ERGM extensions: models for multiple networks and bipartite networks ; 10. Longitudinal models ; 11. Simulation, estimation and goodness of fit ; 12. Illustrations: simulation, estimation and goodness of fit ; 13. Personal attitudes, perceived attitudes and social structures: a social selection model ; 14. How to close a hole: exploring alternative closure mechanisms in inter-organizational network ; 15. Interdependencies between working relations: multivariate ERGMs for advice and satisfaction ; 16. Brain, brawn or optimism? The structure and correlates of emergent military leadership ; 17. An ALAAM analysis of unemployment: the dual importance of who you know and where you live ; 18. Longitudinal changes in face-to-face and text message-mediated friendship networks ; 19. The differential impact of directors' social and financial capital on corporate interlock formation ; 20. Comparing networks: a structural correspondence between behavioural and recall networks ; 21. Modelling social networks: next steps
    Note: MAB0014.001: PIK M 370-13-0140 , MAB0036: m , MAB0455.001: 35 , Includes bibliographical references and index
    Library Location Call Number Availability
    Wissenschaftspark Albert Einstein Gemeinsame Bibliothek A18PIK M 370-13-0140available
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  • 3
    UID:
    almahu_9948317060502882
    Format: xxii, 336 p. : , ill.
    Edition: Electronic reproduction. Ann Arbor, MI : ProQuest, 2015. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries.
    Series Statement: Structural analysis in the social sciences ;
    Content: "Exponential random graph models (ERGMs) are a class of statistical models for social networks. They account for the presence (and absence) of network ties and so provide a model for network structure. An ERGM models a given network in terms of small local tie-based structures, such as reciprocated ties and triangles. A social network can be thought of as being built up of these local patterns of ties, called network configurations xe "network configurations" , which correspond to the parameters in the model. Moreover, these configurations can be considered to arise from local social processes, whereby actors in the network form connections in response to other ties in their social environment. ERGMs are a principled statistical approach to modeling social networks. They are theory-driven in that their use requires the researcher to consider the complex, intersecting and indeed potentially competing theoretical reasons why the social ties in the observed network have arisen. For instance, does a given network structure occur due to processes of homophily xe "actor-relation effects:homophily" , xe "homophily" \t "see actor-relation effects" reciprocity xe "reciprocity" , transitivity xe "transitivity" , or indeed a combination of these? By including such parameters together in the one model a researcher can test these effects one against the other, and so infer the social processes that have built the network. Being a statistical model, an ERGM permits inferences about whether, in our network of interest, there are significantly more (or fewer) reciprocated ties, or triangles (for instance), than we would expect"--
    Note: Machine generated contents note: Introduction Dean Lusher, Johan Koskinen and Garry Robins; 1. What are exponential random graph models Garry Robins and Dean Lusher; 2. The formation of social network structure Dean Lusher and Garry Robins; 3. A simplified account of ERGM as a statistical model Garry Robins and Dean Lusher; 4. An example of ERGM analysis Dean Lusher and Garry Robins; 5. Exponential random graph model fundamentals Johan Koskinene and Galina Daragonova; 6. Dependence graphs and sufficient statistics Johan Koskinen and Galina Daragonova; 7. Social selection, dyadic covariates and geospatial effects Garry Robins and Galina Daragonova; 8. Autologistic actor attribute models Galina Daragonova and Garry Robins; 9. ERGM extensions: models for multiple networks and bipartite networks Peng Wang; 10. Longitudinal models Tom Snijders and Johan Koskinen; 11. Simulation, estimation and goodness of fit Johan Koskinen and Tom Snijders; 12. Illustrations: simulation, estimation and goodness of fit Garry Robins and Dean Lusher; 13. Personal attitudes, perceived attitudes and social structures: a social selection model Dean Lusher and Garry Robins; 14. How to close a hole: exploring alternative closure mechanisms in inter-organizational networks Alessandro Lomi and Francesca Pallotti; 15. Interdependencies between working relations: multivariate ERGMs for advice and satisfaction Yu Zhao and Olaf Rank; 16. Brain, brawn or optimism? The structure and correlates of emergent military leadership Yuval Kalish and Gil Luria; 17. An ALAAM analysis of unemployment: the dual importance of who you know and where you live Galina Daragonova and Philippa Pattison; 18. Longitudinal changes in face-to-face and text message-mediated friendship networks Tasuku Igarashi; 19. The differential impact of directors' social and financial capital on corporate interlock formation Nicholas Harrigan and Matthew Bond; 20. Comparing networks: a structural correspondence between behavioural and recall networks Eric Quintane; 21. Modelling social networks: next steps Philippa Pattison and Tom Snijders.
    Language: English
    Keywords: Electronic books.
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    gbv_1619913070
    Format: xxii, 336 Seiten , Diagramme
    ISBN: 9780521141383 , 9780521193566
    Series Statement: Structural analysis in the social sciences 35
    Content: "This book provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs), as well as a compendium of ERGM methods and illustrative applications"
    Content: "Exponential random graph models (ERGMs) are a class of statistical models for social networks. They account for the presence (and absence) of network ties and so provide a model for network structure. An ERGM models a given network in terms of small local tie-based structures, such as reciprocated ties and triangles. A social network can be thought of as being built up of these local patterns of ties, called network configurations xe "network configurations" , which correspond to the parameters in the model. Moreover, these configurations can be considered to arise from local social processes, whereby actors in the network form connections in response to other ties in their social environment. ERGMs are a principled statistical approach to modeling social networks. They are theory-driven in that their use requires the researcher to consider the complex, intersecting and indeed potentially competing theoretical reasons why the social ties in the observed network have arisen. For instance, does a given network structure occur due to processes of homophily xe "actor-relation effects:homophily" , xe "homophily" \t "see actor-relation effects" reciprocity xe "reciprocity" , transitivity xe "transitivity" , or indeed a combination of these? By including such parameters together in the one model a researcher can test these effects one against the other, and so infer the social processes that have built the network. Being a statistical model, an ERGM permits inferences about whether, in our network of interest, there are significantly more (or fewer) reciprocated ties, or triangles (for instance), than we would expect"
    Content: "This book provides an account of the theoretical and methodological underpinnings of exponential random graph models (ERGMs), as well as a compendium of ERGM methods and illustrative applications"
    Content: "Exponential random graph models (ERGMs) are a class of statistical models for social networks. They account for the presence (and absence) of network ties and so provide a model for network structure. An ERGM models a given network in terms of small local tie-based structures, such as reciprocated ties and triangles. A social network can be thought of as being built up of these local patterns of ties, called network configurations xe "network configurations" , which correspond to the parameters in the model. Moreover, these configurations can be considered to arise from local social processes, whereby actors in the network form connections in response to other ties in their social environment. ERGMs are a principled statistical approach to modeling social networks. They are theory-driven in that their use requires the researcher to consider the complex, intersecting and indeed potentially competing theoretical reasons why the social ties in the observed network have arisen. For instance, does a given network structure occur due to processes of homophily xe "actor-relation effects:homophily" , xe "homophily" \t "see actor-relation effects" reciprocity xe "reciprocity" , transitivity xe "transitivity" , or indeed a combination of these? By including such parameters together in the one model a researcher can test these effects one against the other, and so infer the social processes that have built the network. Being a statistical model, an ERGM permits inferences about whether, in our network of interest, there are significantly more (or fewer) reciprocated ties, or triangles (for instance), than we would expect"
    Note: Hier auch später erschienene, unveränderte Nachdrucke , Literaturverzeichnis: Seite 303-325 , Machine generated contents note: Introduction Dean Lusher, Johan Koskinen and Garry Robins; 1. What are exponential random graph models Garry Robins and Dean Lusher; 2. The formation of social network structure Dean Lusher and Garry Robins; 3. A simplified account of ERGM as a statistical model Garry Robins and Dean Lusher; 4. An example of ERGM analysis Dean Lusher and Garry Robins; 5. Exponential random graph model fundamentals Johan Koskinene and Galina Daragonova; 6. Dependence graphs and sufficient statistics Johan Koskinen and Galina Daragonova; 7. Social selection, dyadic covariates and geospatial effects Garry Robins and Galina Daragonova; 8. Autologistic actor attribute models Galina Daragonova and Garry Robins; 9. ERGM extensions: models for multiple networks and bipartite networks Peng Wang; 10. Longitudinal models Tom Snijders and Johan Koskinen; 11. Simulation, estimation and goodness of fit Johan Koskinen and Tom Snijders; 12. Illustrations: simulation, estimation and goodness of fit Garry Robins and Dean Lusher; 13. Personal attitudes, perceived attitudes and social structures: a social selection model Dean Lusher and Garry Robins; 14. How to close a hole: exploring alternative closure mechanisms in inter-organizational networks Alessandro Lomi and Francesca Pallotti; 15. Interdependencies between working relations: multivariate ERGMs for advice and satisfaction Yu Zhao and Olaf Rank; 16. Brain, brawn or optimism? The structure and correlates of emergent military leadership Yuval Kalish and Gil Luria; 17. An ALAAM analysis of unemployment: the dual importance of who you know and where you live Galina Daragonova and Philippa Pattison; 18. Longitudinal changes in face-to-face and text message-mediated friendship networks Tasuku Igarashi; 19. The differential impact of directors' social and financial capital on corporate interlock formation Nicholas Harrigan and Matthew Bond; 20. Comparing networks: a structural correspondence between behavioural and recall networks Eric Quintane; 21. Modelling social networks: next steps Philippa Pattison and Tom Snijders.
    Additional Edition: Erscheint auch als Online-Ausgabe Exponential random graph models for social networks Cambridge : Cambridge University Press, 2013 ISBN 0511894708
    Additional Edition: ISBN 1139841963
    Additional Edition: ISBN 1139839586
    Additional Edition: ISBN 9781139839587
    Additional Edition: ISBN 9781139841962
    Additional Edition: ISBN 9780511894701
    Additional Edition: Erscheint auch als Online-Ausgabe Exponential random graph models for social networks Cambridge : Cambridge University Press, 2013 ISBN 9780511894701
    Language: English
    Subjects: Sociology
    RVK:
    RVK:
    Keywords: Netzwerkanalyse ; Graphentheoretisches Modell ; Aufsatzsammlung
    Library Location Call Number Availability
    UB Potsdam Handapparat3518possibly available
    UB Potsdam Handapparat3412possibly available
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  • 5
    UID:
    almafu_BV041241315
    Format: 1 Online-Ressource (XXII, 336 S.) : , Ill., graph. Darst.
    ISBN: 978-1-13-984196-2 , 978-0-51-189470-1 , 9781139844321
    Series Statement: Structural analysis in the social sciences 35
    Additional Edition: Erscheint auch als Druck-Ausgabe, Hardcover ISBN 978-0-521-19356-6
    Additional Edition: Erscheint auch als Druck-Ausgabe, Paperback ISBN 978-0-521-14138-3
    Language: English
    Subjects: Sociology
    RVK:
    Keywords: Netzwerkanalyse ; Graphentheoretisches Modell ; Aufsatzsammlung ; Aufsatzsammlung
    Library Location Call Number Volume/Issue/Year Availability
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