Advanced RSiena workshop

January 25-26, 2024

Possible Topics

Beyond homophily: Effects of actor covariates on networks.

Beyond Homophily,
slides for
Tom A.B. Snijders and Alessandro Lomi (2019). Beyond Homophily: Incorporating Actor Variables in Statistical Network Models.
Network Science, 7, 1-19.

Associated with this paper is the script SelectionTables.r which is available from the scripts page.

Selection tables and influence tables.

For selection tables, see above, and p. 24-42 of the slides:

Model Specification Recommendations for Siena: Siena_ModelSpec_s.pdf (slides)

For influence tables:

Script : InfluenceTables.r;

RSiena Manual, Section 13.4.

Also see p. 42 of Statistical Methods for Social Network Dynamics, C: Networks and Behavior: Net_longi7_C_s.pdf

Assessment and visualization of the relative size of selection and influence .

A script illustrating the numerical description of the distinction between selection and influence by a decomposition of the Moran statistic according to Steglich, Snijders & Pearson (2010, Sociological Methodology):

MoranDecompositionExample.R.

Multivariate networks.

Slide presentations:
- Analyzing the Joint Dynamics of Several Networks (slides)
  Analyzing the Joint Dynamics of Several Networks (for printing)
Examples:
- Alona Labun, Rafael Wittek, and Christian Steglich (2016).
  The co-evolution of power and friendship networks in an organization.
  Network Science, 4, 364-384.
  DOI: http://dx.doi.org/10.1017/nws.2016.7
Literature :
- Tom A.B. Snijders, Alessandro Lomi, and Vanina Jasmine Torló (2013).
  A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice.
  Social Networks, 35, 265-276.
  DOI: http://dx.doi.org/10.1016/j.socnet.2012.05.005.
  In Figure 2, Y_{ia} and Y_{ja} should be interchanged.

Co-evolution of two-mode and one-mode networks.

Slide presentations :
- The dynamics of two-mode networks (slides)
  The dynamics of two-mode networks (for printing)
- The co-evolution of multiple networks: one-mode and two-mode (slides)
  The co-evolution of multiple networks: one-mode and two-mode (for printing).
Scripts :
- g160_Onemode_Twomode.r script for the example in the slides using the Glasgow Teenage Friends and Lifestyle Study data.
- RscriptSienaBipartite.R an example of co-evolution of a one-mode and several two-mode networks, using the same data set.
  This is an old script, written before the current high standards of convergence were followed.
Examples :
- Per Block, Lauren C. Heathcote and Stephanie Burnett Heyes (2018).
  Social interaction and pain: An arctic expedition.
  Social Science and Medicine, 196, 47-55.
  DOI: https://doi.org/10.1016/j.socscimed.2017.10.028
- Kayo Fujimoto, Tom A.B. Snijders, and Thomas W. Valente (2018).
  Multivariate dynamics of one-mode and two-mode networks: Explaining similarity in sports participation among friends.
  Network Science, 6, 370-395.
  DOI: http://dx.doi.org/10.1017/nws.2018.11
- Alessandro Lomi and Christoph Stadtfeld (2014).
  Social Networks and Social Settings: Developing a Coevolutionary View.
  KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 66, 395-415.
  DOI: http://dx.doi.org/10.1007/s11577-014-0271-8.
Literature :
- Tom A.B. Snijders, Alessandro Lomi, and Vanina Jasmine Torló (2013).
  A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice.
  Social Networks, 35, 265-276.
  DOI: http://dx.doi.org/10.1016/j.socnet.2012.05.005.
  In Figure 2, Y_{ia} and Y_{ja} should be interchanged.

Valued networks (two kinds: networks with weak and strong ties; signed networks).

Slide presentations :
- Analysing the dynamics of valued networks (slides)
  Analysing the dynamics of valued networks (for printing).
Scripts :
- RscriptSienaOrdered.R an example of modeling a network with ordered ties (i.e., valued ties with a small set of ordered categories), by representing them as multiple, ordered networks, using the van de Bunt students data set.
- vdB_orderedNewer2345.R script for the example in the slides, also using the van de Bunt students data set.
Examples :
- Timon Elmer, Zsófia Boda, and Christoph Stadtfeld (2017).
  The co-evolution of emotional well-being with weak and strong friendship ties.
  Network Science, 5, 278-307.
  DOI: https://doi.org/10.1017/nws.2017.20
- Zsófia Boda, Bálint Néray, and Tom A. B. Snijders (2020).
  The Dynamics of Interethnic Friendships and Negative Ties in Secondary School: The Role of Peer-Perceived Ethnicity.
  Social Psychology Quarterly, 83, 342-362.
  DOI: http://dx.doi.org/10.1177/0190272520907594
  Multivariate and also multilevel (uses sienaBayes).

Parameter interpretation: semi-standardized parameters: entropy-based approach to explained variation.

Slide presentations :
- Effect Sizes for Stochastic Actor-oriented Models (slides)
  Effect Sizes for Stochastic Actor-oriented Models (for printing).
Scripts :
- vdB_effsize.R script for the example in the slides ("Question 3"), also using the van de Bunt students data set.
- Not related to semi-standardized parameters or entropy:
  A useful script for parameter interpretation for effects of actor variables on networks (see Section 13.3 in the manual):
  SelectionTables.r.

Non-directed networks.

Slide presentations :
- Analysing the dynamics of non-directed networks (slides)
  Analysing the dynamics of non-directed networks (for printing).
Scripts :
- RscriptSienaSymmetric.R a brief example of modeling a non-directed network, using the s50 data set.
- Vervet_Monkeys3.R script for the example in the slides using Sebastian Sosa's data set of Vervet Monkeys.
Examples :
- Christèle Borgeaud, Sebastian Sosa, Cédric Sueur, Redouan Bshary, and Erica van de Waal (2016).
  Intergroup Variation of Social Relationships in Wild Vervet Monkeys: A Dynamic Network Approach.
  Frontiers in Psychology, 7, 915.
  DOI: http://dx.doi.org/10.3389/fpsyg.2016.00915
- Leonardo Corbo, Raffaele Corrado, and Simone Ferriani (2016).
  A New Order of Things: Network Mechanisms of Field Evolution in the Aftermath of an Exogenous Shock.
  Organization Studies, 37, 323-348.
  DOI: https://doi.org/10.1177/0170840615613373
- Sebastian Sosa, Peng Zhang, and Guénaël Cabanes (2017).
  Social networks dynamics revealed by temporal analysis: An example in a non-human primate (Macaca sylvanus) in "La Forêt des Singes".
  American Journal of Primatology, 79(6), e22662.
  DOI: http://dx.doi.org/10.1002/ajp.22662.
Literature :
- Snijders, Tom A.B. and Pickup, Mark (2017).
  Stochastic Actor-Oriented Models for Network Dynamics.
  Pp. 221-247 in Oxford Handbook of Political Networks, edited by Jennifer Nicoll Victor, Alexander H. Montgomery, and Mark Lubell. Oxford: Oxford University Press.
  DOI: http://dx.doi.org/10.1093/oxfordhb/9780190228217.013.10.
  Also available in OUP Handbooks-online.
  (Gives a general introduction, and also explains the Stochastic Actor-Oriented Model for non-directed networks.)

Multilevel longitudinal network estimation using sienaBayes.

Slide presentations :
- Multilevel analysis of network dynamics (slides)
  Multilevel analysis of network dynamics (for printing)
- Network dynamics using sienaBayes (slides)
  Network dynamics using sienaBayes (for printing)
- An example of multilevel analysis of network dynamics using sienaBayes.
- One-mode - two-mode co-evolution for studying social influence on behaviour , a presentation about the example in Koskinen & Snijders (2023) not highlighting the estimation by sienaBayes.
- Goodness of Fit for Multilevel Dynamic Network Models
Scripts :
- RscriptsienaBayes_4.r, an example script for the function sienaBayes in multiSiena, using a multi-group data set from Andrea Knecht's data, of which a description of one class is to be found here.
  (This script does not precisely follow the recommendations made in the slides above. Well, the recommendations are approximate anyway.)
- BayesPlots.r, a collection of plotting functions for sienaBayesFit objects, produced by sienaBayes.
- The script used for Koskinen and Snijders (2023).
Examples :
- Isabel J. Raabe, Zsófia Boda and Christoph Stadtfeld (2019).
  The social pipeline: How friend influence and peer exposure widen the STEM gender gap.
  Sociology of Education, 92, 105-123.
  DOI: https://doi.org/10.1177/0038040718824095
- Zsófia Boda, Bálint Néray, and Tom A.B. Snijders (2020).
  The Dynamics of Interethnic Friendships and Negative Ties in Secondary School: The Role of Peer-Perceived Ethnicity.
  Social Psychology Quarterly, 83, 342-362.
  DOI: http://dx.doi.org/10.1177/0190272520907594
  Multivariate and also multilevel.
Literature :
- Johan Koskinen and Tom A.B. Snijders (2023).
  Multilevel longitudinal analysis of social networks.
  Journal of the Royal Statistical Society, Series A, 186, 376-400.
  DOI: https://doi.org/10.1093/jrsssa/qnac009
  This is an explanation of the statistical theory behind the sienaBayes function for multilevel longitudinal network analysis. It also presents an example of one-mode - two-mode network coevolution.

Maximum likelihood estimation .

Slides:
Tom A.B. Snijders, Maximum Likelihood Estimation in RSiena.

Programming new effects .

Slides:
Tom A.B. Snijders Coding Effects for RSiena

Also: Chapter 18 of the RSiena Manual.

Joining the GitHub team.

The new stocnet at GitHub!.

Back to the main Siena page

	Advanced RSiena workshop January 25-26, 2024


	Possible Topics Beyond homophily: Effects of actor covariates on networks. Beyond Homophily, slides for Tom A.B. Snijders and Alessandro Lomi (2019). Beyond Homophily: Incorporating Actor Variables in Statistical Network Models. Network Science, 7, 1-19. Associated with this paper is the script SelectionTables.r which is available from the scripts page. Selection tables and influence tables. For selection tables, see above, and p. 24-42 of the slides: Model Specification Recommendations for Siena: Siena_ModelSpec_s.pdf (slides) For influence tables: Script : InfluenceTables.r; RSiena Manual, Section 13.4. Also see p. 42 of Statistical Methods for Social Network Dynamics, C: Networks and Behavior: Net_longi7_C_s.pdf Assessment and visualization of the relative size of selection and influence . A script illustrating the numerical description of the distinction between selection and influence by a decomposition of the Moran statistic according to Steglich, Snijders & Pearson (2010, Sociological Methodology): MoranDecompositionExample.R. Multivariate networks. Slide presentations: Analyzing the Joint Dynamics of Several Networks (slides) Analyzing the Joint Dynamics of Several Networks (for printing) Examples: Alona Labun, Rafael Wittek, and Christian Steglich (2016). The co-evolution of power and friendship networks in an organization. Network Science, 4, 364-384. DOI: http://dx.doi.org/10.1017/nws.2016.7 Literature : Tom A.B. Snijders, Alessandro Lomi, and Vanina Jasmine Torló (2013). A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice. Social Networks, 35, 265-276. DOI: http://dx.doi.org/10.1016/j.socnet.2012.05.005. In Figure 2, Y_{ia} and Y_{ja} should be interchanged. Co-evolution of two-mode and one-mode networks. Slide presentations : The dynamics of two-mode networks (slides) The dynamics of two-mode networks (for printing) The co-evolution of multiple networks: one-mode and two-mode (slides) The co-evolution of multiple networks: one-mode and two-mode (for printing). Scripts : g160_Onemode_Twomode.r script for the example in the slides using the Glasgow Teenage Friends and Lifestyle Study data. RscriptSienaBipartite.R an example of co-evolution of a one-mode and several two-mode networks, using the same data set. This is an old script, written before the current high standards of convergence were followed. Examples : Per Block, Lauren C. Heathcote and Stephanie Burnett Heyes (2018). Social interaction and pain: An arctic expedition. Social Science and Medicine, 196, 47-55. DOI: https://doi.org/10.1016/j.socscimed.2017.10.028 Kayo Fujimoto, Tom A.B. Snijders, and Thomas W. Valente (2018). Multivariate dynamics of one-mode and two-mode networks: Explaining similarity in sports participation among friends. Network Science, 6, 370-395. DOI: http://dx.doi.org/10.1017/nws.2018.11 Alessandro Lomi and Christoph Stadtfeld (2014). Social Networks and Social Settings: Developing a Coevolutionary View. KZfSS Kölner Zeitschrift für Soziologie und Sozialpsychologie, 66, 395-415. DOI: http://dx.doi.org/10.1007/s11577-014-0271-8. Literature : Tom A.B. Snijders, Alessandro Lomi, and Vanina Jasmine Torló (2013). A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice. Social Networks, 35, 265-276. DOI: http://dx.doi.org/10.1016/j.socnet.2012.05.005. In Figure 2, Y_{ia} and Y_{ja} should be interchanged. Valued networks (two kinds: networks with weak and strong ties; signed networks). Slide presentations : Analysing the dynamics of valued networks (slides) Analysing the dynamics of valued networks (for printing). Scripts : RscriptSienaOrdered.R an example of modeling a network with ordered ties (i.e., valued ties with a small set of ordered categories), by representing them as multiple, ordered networks, using the van de Bunt students data set. vdB_orderedNewer2345.R script for the example in the slides, also using the van de Bunt students data set. Examples : Timon Elmer, Zsófia Boda, and Christoph Stadtfeld (2017). The co-evolution of emotional well-being with weak and strong friendship ties. Network Science, 5, 278-307. DOI: https://doi.org/10.1017/nws.2017.20 Zsófia Boda, Bálint Néray, and Tom A. B. Snijders (2020). The Dynamics of Interethnic Friendships and Negative Ties in Secondary School: The Role of Peer-Perceived Ethnicity. Social Psychology Quarterly, 83, 342-362. DOI: http://dx.doi.org/10.1177/0190272520907594 Multivariate and also multilevel (uses sienaBayes). Parameter interpretation: semi-standardized parameters: entropy-based approach to explained variation. Slide presentations : Effect Sizes for Stochastic Actor-oriented Models (slides) Effect Sizes for Stochastic Actor-oriented Models (for printing). Scripts : vdB_effsize.R script for the example in the slides ("Question 3"), also using the van de Bunt students data set. Not related to semi-standardized parameters or entropy: A useful script for parameter interpretation for effects of actor variables on networks (see Section 13.3 in the manual): SelectionTables.r. Non-directed networks. Slide presentations : Analysing the dynamics of non-directed networks (slides) Analysing the dynamics of non-directed networks (for printing). Scripts : RscriptSienaSymmetric.R a brief example of modeling a non-directed network, using the s50 data set. Vervet_Monkeys3.R script for the example in the slides using Sebastian Sosa's data set of Vervet Monkeys. Examples : Christèle Borgeaud, Sebastian Sosa, Cédric Sueur, Redouan Bshary, and Erica van de Waal (2016). Intergroup Variation of Social Relationships in Wild Vervet Monkeys: A Dynamic Network Approach. Frontiers in Psychology, 7, 915. DOI: http://dx.doi.org/10.3389/fpsyg.2016.00915 Leonardo Corbo, Raffaele Corrado, and Simone Ferriani (2016). A New Order of Things: Network Mechanisms of Field Evolution in the Aftermath of an Exogenous Shock. Organization Studies, 37, 323-348. DOI: https://doi.org/10.1177/0170840615613373 Sebastian Sosa, Peng Zhang, and Guénaël Cabanes (2017). Social networks dynamics revealed by temporal analysis: An example in a non-human primate (Macaca sylvanus) in "La Forêt des Singes". American Journal of Primatology, 79(6), e22662. DOI: http://dx.doi.org/10.1002/ajp.22662. Literature : Snijders, Tom A.B. and Pickup, Mark (2017). Stochastic Actor-Oriented Models for Network Dynamics. Pp. 221-247 in Oxford Handbook of Political Networks, edited by Jennifer Nicoll Victor, Alexander H. Montgomery, and Mark Lubell. Oxford: Oxford University Press. DOI: http://dx.doi.org/10.1093/oxfordhb/9780190228217.013.10. Also available in OUP Handbooks-online. (Gives a general introduction, and also explains the Stochastic Actor-Oriented Model for non-directed networks.) Multilevel longitudinal network estimation using sienaBayes. Slide presentations : Multilevel analysis of network dynamics (slides) Multilevel analysis of network dynamics (for printing) Network dynamics using sienaBayes (slides) Network dynamics using sienaBayes (for printing) An example of multilevel analysis of network dynamics using sienaBayes. One-mode - two-mode co-evolution for studying social influence on behaviour , a presentation about the example in Koskinen & Snijders (2023) not highlighting the estimation by sienaBayes. Goodness of Fit for Multilevel Dynamic Network Models Scripts : RscriptsienaBayes_4.r, an example script for the function sienaBayes in multiSiena, using a multi-group data set from Andrea Knecht's data, of which a description of one class is to be found here. (This script does not precisely follow the recommendations made in the slides above. Well, the recommendations are approximate anyway.) BayesPlots.r, a collection of plotting functions for sienaBayesFit objects, produced by sienaBayes. The script used for Koskinen and Snijders (2023). Examples : Isabel J. Raabe, Zsófia Boda and Christoph Stadtfeld (2019). The social pipeline: How friend influence and peer exposure widen the STEM gender gap. Sociology of Education, 92, 105-123. DOI: https://doi.org/10.1177/0038040718824095 Zsófia Boda, Bálint Néray, and Tom A.B. Snijders (2020). The Dynamics of Interethnic Friendships and Negative Ties in Secondary School: The Role of Peer-Perceived Ethnicity. Social Psychology Quarterly, 83, 342-362. DOI: http://dx.doi.org/10.1177/0190272520907594 Multivariate and also multilevel. Literature : Johan Koskinen and Tom A.B. Snijders (2023). Multilevel longitudinal analysis of social networks. Journal of the Royal Statistical Society, Series A, 186, 376-400. DOI: https://doi.org/10.1093/jrsssa/qnac009 This is an explanation of the statistical theory behind the sienaBayes function for multilevel longitudinal network analysis. It also presents an example of one-mode - two-mode network coevolution. Maximum likelihood estimation . Slides: Tom A.B. Snijders, Maximum Likelihood Estimation in RSiena. Programming new effects . Slides: Tom A.B. Snijders Coding Effects for RSiena Also: Chapter 18 of the RSiena Manual. Joining the GitHub team. The new stocnet at GitHub!.



	Back to the main Siena page