Jürgen Lerner

I'm researcher at the Department of Computer and Information Science of the University of Konstanz, where from 2017 to 2025 I'm leading a project on statistical analysis of social networks, funded by Deutsche Forschungsgemeinschaft (DFG 321869138).  My research interests include social network analysis, computational social science, and statistical network modeling. I'm thrilled by applications of network analysis in various disciplines of the social sciences and beyond. One network analysis method - relational (hyper-)event models - turned out to be particularly relevant with applications in diverse research areas, including organization science, public health, bibliometrics, international relations, political science / history, sociology, criminology, biology / collective behavior, communication, social psychology, and open peer-production. During three semesters from 2022 - 2023 I was interim professor for Computational Social Sciences and Humanities at the RWTH Aachen.

Contact: juergen.lerner@gmail.com and juergen.lerner@uni-konstanz.de 

Research interests

• Social network analysis

• Computational social science

• Statistical network models

• Machine learning

• Open peer-production

Teaching

(recent years)

• Winter 2024/2025: Lecture Network modeling and machine learning

• Summer 2023: Lecture Social Networks

• Summer 2023: Project Computational social systems / Social data science

• Winter 2022/2023: Lecture Social data science

• Winter 2022/2023: Project Computational social systems / Social data science

• Summer 2022: Lecture Social Networks

• Summer 2022: Project Computational social systems / Social data science

• Winter 2021/2022: Lecture Network modeling and relational machine learning

• Winter 2020/2021: Lecture Network modeling and relational machine learning

• Summer 2020: Exercises for Konzepte der Informatik

• Winter 2019/2020: Seminar Sentiment analysis and word embeddings

• Summer 2019: Seminar Link prediction

• Winter 2018/2019: Lecture Network Modeling

Software

• event network analyzer (eventnet) software for the statistical analysis of networks of relational events

• EgoNet2GraphML conversion of EgoNet interview files to GraphML (and computing clustered graphs)

• SocialCapitalCompanion personal network diaries on mobile devices

• visone visualization and analysis of social networks

• WikiEvent extracting relational events from Wikipedia edit histories

Publications

Journal articles

• Bianca-Elena Mihaila, Marian-Gabriel Hâncean, Matjaž Perc, Jürgen Lerner, Iulian Oana, Marius Geanta, José Luis Molina, and Cosmina Cioroboiu: Cross-sectional personal network analysis of adult smoking in rural areas. Royal Society Open Science, 11:241459, 2024. https://doi.org/10.1098/rsos.241459

• Iulian Oana, Marian-Gabriel Hâncean, Matjaž Perc, Jürgen Lerner, Bianca-Elena Mihaila, Marius Geanta, José Luis Molina, Isabela Tinca, and Carolina Espina: Online Media Use and COVID-19 Vaccination in Real-World Personal Networks: Quantitative Study. Journal of Medical Internet Research, 26:e58257, 2024.http://dx.doi.org/10.2196/58257

• David Bright, Jürgen Lerner, and Giovanni Radhitio Putra Sadewo. Examining co-offending and re-offending across crime categories using relational hyperevent models. Journal of Criminology, 2024. https://doi.org/10.1177/26338076241272864

• Jürgen Lerner, Marian-Gabriel Hâncean, and Alessandro Lomi: Relational hyperevent models for the coevolution of coauthoring and citation networks. Journal of the Royal Statistical Society Series A: Statistics in Society, qnae068, 2024. https://doi.org/10.1093/jrsssa/qnae068

• Katharina Burgdorf, Mark Wittek, and Jürgen Lerner: Communities of Style: Artistic Transformation and Social Cohesion in Hollywood, 1930 to 1999. Socius, 10, 23780231241257334, 2024. https://doi.org/10.1177/23780231241257334

• Marian-Gabriel Hâncean, Jürgen Lerner, Matjaž Perc, José Luis Molina, and Marius Geantă: Assortative mixing of opinions about COVID-19 vaccination in personal networks. Scientific Reports, 14:3385, 2024. https://doi.org/10.1038/s41598-024-53825-3

• David Bright, Jürgen Lerner, Giovanni Radhitio Putra Sadewo, and Chad Whelan. Offence versatility among co-offenders: A dynamic network analysis. Social Networks, 2024. DOI: 10.1016/j.socnet.2023.10.003

• Michael Kings, Josh J. Arbon, Guillam E. McIvor, Martin Whitaker, Andrew N. Radford, Jürgen Lerner, and Alex Thornton (2023). Wild jackdaws can selectively adjust their social associations while preserving valuable long-term relationships. Nature Communications. DOI: https://doi.org/10.1038/s41467-023-40808-7. (See news coverage in The Guardian.)

• David Bright, Giovanni Radhitio Putra Sadewo, Jürgen Lerner, Timothy Cubitt, Christopher Dowling, and Anthony Morgan: Investigating the Dynamics of Outlaw Motorcycle Gang Co-Offending Networks: The Utility of Relational Hyper Event Models. Journal of Quantitative Criminology, 2023. DOI: 10.1007/s10940-023-09576-x

• Marco Tonellato, Stefano Tasselli, Guido Conaldi, Jürgen Lerner, and Alessandro Lomi: A Microstructural Approach to Self-Organizing: The Emergence of Attention Networks. Organization Science, 2023. https://doi.org/10.1287/orsc.2023.1674 

• Jürgen Lerner and Alessandro Lomi: Relational hyperevent models for polyadic interaction networks. Journal of the Royal Statistical Society: Series A, 2023. https://doi.org/10.1093/jrsssa/qnac012 

• Jürgen Lerner and Marian-Gabriel Hâncean: Micro-level network dynamics of scientific collaboration and impact: relational hyperevent models for the analysis of co-author networks. Network Science, 11(1):5-35, 2023. https://www.doi.org/10.1017/nws.2022.29 

• Marian-Gabriel Hâncean, Jürgen Lerner, Matjaž Perc, Iulian Oana, David-Andrei Bunaciu, Adelina Alexandra Stoica, and Maria Cristina Ghita: Occupations and their impact on the spreading of COVID-19 in urban communities. Scientific Reports, 12:14115, 2022. https://doi.org/10.1038/s41598-022-18392-5

• Marian-Gabriel Hâncean, Maria Cristina Ghita, Matjaž Perc, Jürgen Lerner, Iulian Oana, Bianca-Elena Mihaila, Adelina Alexandra Stoica, and David-Andrei Bunaciu: Disaggregated data on age and sex for the first 250 days of the COVID-19 pandemic in Bucharest, Romania. Scientific Data, 9:253. https://doi.org/10.1038/s41597-022-01374-7

• Jürgen Lerner  and Alessandro Lomi: A dynamic model for the mutual constitution of individuals and events. Journal of Complex Networks, 10(2):cnac004, 2022. https://doi.org/10.1093/comnet/cnac004 (Link to the Supporting Information document.)

• Marian-Gabriel Hâncean, Jürgen Lerner, Matjaž Perc, Maria Cristina Ghita, David-Andrei Bunaciu, Adelina Alexandra Stoica, and Bianca-Elena Mihaila: The role of age in the spreading of COVID-19 across a social network in Bucharest. Journal of Complex Networks, 9(4), 2021. https://doi.org/10.1093/comnet/cnab026

• Jürgen Lerner, Alessandro Lomi, John Mowbray, Neil Rollings, and Mark Tranmer: Dynamic network analysis of contact diaries. Social Networks, 66:224-236, 2021. https://doi.org/10.1016/j.socnet.2021.04.001

• Marian-Gabriel Hâncean, Matjaž Perc, and Jürgen Lerner: The coauthorship networks of the most productive European researchers. Scientometrics, 126:201-224, 2021. https://doi.org/10.1007/s11192-020-03746-5 

• Marian-Gabriel Hancean, Matjaz Perc, and Jürgen Lerner: Early spread of COVID-19 in Romania: imported cases from Italy and human-to-human transmission networks. Royal Society Open Science, 7:200780, 2020.

• Jürgen Lerner and Alessandro Lomi: Reliability of relational event model estimates under sampling: how to fit a relational event model to 360 million dyadic events. Network Science, 8(1):97-135, 2020.

• Jürgen Lerner and Alessandro Lomi: The free encyclopedia that anyone can dispute: An analysis of the micro-structural dynamics of positive and negative relations in the production of contentious Wikipedia articles. Social Networks, 60:11-25, 2020. (Access to the accepted manuscript.)

•  Jürgen Lerner and Alessandro Lomi: Team diversity, polarization, and productivity in online peer-production. Social Network Analysis and Mining, 9(29), 2019. (Access to the accepted manuscript.)

• Jürgen Lerner and Alessandro Lomi: Knowledge categorization affects popularity and quality of Wikipedia articles. PLoS ONE, 13(1):e0190674, 2018.

• Jürgen Lerner and Alessandro Lomi: The Third Man: hierarchy formation in Wikipedia. Applied Network Science, 2(1):24, 2017.

• Jürgen Lerner: Structural Balance in Signed Networks: Separating the Probability to Interact from the Tendency to Fight. Social Networks, 45:66-77, 2016. (Access to the accepted manuscript.)

• Hugo Valenzuela-García, Jose Luis Molina, Miranda J. Lubbers, Alejandro García-Macías, Judith Pamplona, and Jürgen Lerner: On Heterogeneous and Homogeneous Networks in a Multilayered Reality. Societies, 4:85-104, 2014. 

• Jürgen Lerner, Natalie Indlekofer, Bobo Nick and Ulrik Brandes: Conditional Independence in Dynamic Networks. Journal of Mathematical Psychology, 57(6):275-283, 2013. 

• Jürgen Lerner, Margit Bussmann, Tom A.B. Snijders, and Ulrik Brandes: Modeling frequency and type of interaction in event networks. Corvinus Journal of Sociology and Social Policy, 4(1):3-32, 2013.

• Jürgen Lerner, Patrick Kenis, Denise van Raaij, and Ulrik Brandes: Will they stay or will they go? How network properties of WebICs predict dropout rates of valuable Wikipedians. European Management Journal, 29(5):404-413, 2011. (A tutorial on how to reproduce the analysis in this paper can be found in the visone wiki's tutorial on Wikipedia edit networks.)

• Ulrik Brandes, Jürgen Lerner and Uwe Nagel: Network Ensemble Clustering with Latent Roles. Advances in Data Analysis and Classification, 5(2):81-94, 2011. 

• Ulrik Brandes and Jürgen Lerner: Structural Similarity: Spectral Methods for Relaxed Blockmodeling. Journal of Classification 27(3):279-306, 2010.

• Miranda J. Lubbers, Jose Luis Molina, Jürgen Lerner, Ulrik Brandes, Javier Avila, and Christopher McCarty: Longitudinal Analysis of Personal Networks. The Case of Argentinean Migrants in Spain. Social Networks 32(1):91-104, 2010.

• Jose Luis Molina, Jürgen Lerner, and Silvia Gomez Mestres: Patrones de Cambio de las Redes Personales de Inmigrantes en Cataluña. REDES, 15:50-63, 2008.

• Ulrik Brandes and Jürgen Lerner: Visual Analysis of Controversy in User-generated Encyclopedias. Information Visualization, 7:34-48, 2008.

• Ulrik Brandes, Daniel Fleischer, and Jürgen Lerner: Summarizing Dynamic Bipolar Conflict Structures. IEEE Transactions on Visualization and Computer Graphics, 12(6):1486-1499, 2006. (Example data and animations are available <here>.)

Articles in peer-reviewed conference proceedings

• Jürgen Lerner and Alessandro Lomi: The Network Structure of Successful Collaboration in Wikipedia. Proc. 52nd Hawaii International Conference on System Sciences (HICSS 2019), pages 2622-2631. (Access to the accepted manuscript.)

• Jürgen Lerner and Alessandro Lomi: Let's talk about refugees: Network effects drive contributor attention to Wikipedia articles about migration-related topics. Proc. Complex Networks and Their Applications VII (Complex Networks 2018), pages 211-222. Springer International Publishing, 2019. (Access to the accepted manuscript.)

• Jürgen Lerner and Alessandro Lomi: Diverse Teams Tend to Do Good Work in Wikipedia (but Jacks of All Trades Don't). In:  Ulrik Brandes, Chandan Reddy, Andrea Tagarelli (eds.), Proc. 2018 Intl. Conf. Advances in Social Network Analysis and Mining (ASONAM 2018), pages 214 - 221. IEEE Computer Society, 2018. (Access to the accepted manuscript.)

• Jürgen Lerner and Alessandro Lomi: Dominance, Deference, and Hierarchy Formation in Wikipedia Edit-Networks. In: Cherifi H., Gaito S., Quattrociocchi W., Sala A. (eds), Complex Networks & Their Applications V. Springer-Verlag, 2017. (Access to the accepted manuscript for non-commercial and educational purposes.)

• Ulrik Brandes, Jürgen Lerner, Bobo Nick and Steffen Rendle: Network Effects on Interest Rates in Online Social Lending. In Proc. INFORMATIK 2011 - 4. Workshop Digitale soziale Netwerke, GI Edition - Lecture Notes in Informatics (LNI), vol. 192, 2011.

• Jerome Kunegis, Stephan Schmidt, Andreas Lommatzsch, Jürgen Lerner, Ernesto W. De Luca, and Sahin Albayrak: Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization. In: Proc. SIAM Intl. Conf. on Data Mining, 2010.

• Ulrik Brandes, Jürgen Lerner, Miranda J. Lubbers, Christopher McCarty, Jose; Luis Molina and Uwe Nagel: Recognizing modes of acculturation in personal networks of migrants. In: Proc. 6th Conf. Applications of Social Network Analysis (ASNA 2009), Procedia - Social Behavioral and Sciences, vol. 4, pp. 4-13. Elsevier, 2010. 

• Ulrik Brandes, Jürgen Lerner, and Tom A. B. Snijders: Networks Evolving Step by Step: Statistical Analysis of Dyadic Event Data. In: Proc. 2009 Intl. Conf. Advances in Social Network Analysis and Mining (ASONAM 2009), pp.200-205. IEEE Computer Society, 2009.

• Ulrik Brandes, Jürgen Lerner, Uwe Nagel, and Bobo Nick: Structural Trends in Network Ensembles. In: Proc. Intl. Workshop Complex Networks (CompleNet 2009), pp.83-97. Springer-Verlag, 2009.

• Ulrik Brandes, Patrick Kenis, Jürgen Lerner, and Denise van Raaij: Network Analysis of Collaboration Structure in Wikipedia. In: Proc. 18th Intl. World Wide Web Conference (WWW 2009). (A tutorial on how to reproduce the analysis in this paper can be found in the visone wiki's tutorial on Wikipedia edit networks.)

• Ulrik Brandes, Patrick Kenis, Jürgen Lerner, and Denise van Raaij: Is Editing More Rewarding Than Discussion? A Statistical Framework to Estimate Causes of Dropout from Wikipedia. In: Proc. 1st Intl. Workshop Motivation and Incentives on the Web (Webcentives'09) at the 18th Intl. World Wide Web Conference (WWW 2009).

• Ulrik Brandes, Jürgen Lerner, Miranda J. Lubbers, Chris McCarty and Jose; Luis Molina: Visual Statistics for Collections of Clustered Graphs. In: Proc. IEEE Pacific Visualization Symp. (PacificVis'08), pp. 47-54. IEEE Computer Society, 2008. (A guide on how to apply the techniques proposed in the paper can be found in the visone wiki's personal networks tutorial.)

• Ulrik Brandes and Jürgen Lerner: Visual Analysis of Controversy in User-generated Encyclopedias. In: Proc. IEEE Symp. Visual Analytics Science and Technology (VAST'07), pp. 179-186. IEEE Computer Society, 2007.

• Ulrik Brandes and Jürgen Lerner: Revision and Co-revision in Wikipedia. Proc. Intl. Workshop Bridging the Gap Between Semantic Web and Web 2.0, 4th Europ. Semantic Web Conf. (ESWC'07), 2007.

• Ulrik Brandes and Jürgen Lerner: Role-equivalent Actors in Networks. Proc. ICFCA'07 Satellite Workshop Social Network Analysis and Conceptual Structures, 2007.

• Ulrik Brandes and Jürgen Lerner: Coloring Random 3-Colorable Graphs with Non-Uniform Edge Probabilities. Proc. 31st Intl. Symp. Mathematical Foundations of Computer Science (MFCS'06), pp. 202-213. Springer-Verlag, 2006.

• Ulrik Brandes, Martin Hoefer, and Jürgen Lerner: WordSpace - Visual Summary of Text Corpora. Proc. IST/SPIE's 18th Ann. Intl. Symp. Electronic Imaging (VDA'06), SPIE Vol. 6060 60600N, 2006.

• Ulrik Brandes, Daniel Fleischer, and Jürgen Lerner: Highlighting Conflict Dynamics in Event Data. Proc. IEEE Symp. Information Visualization (InfoVis'05), pp. 103-110. IEEE Computer Society, 2005. (Example data and animations are available <here>.)

• Ulrik Brandes, Jürgen Lerner, and Christian Pich: GXL to GraphML and Vice Versa with XSLT. Proc. 2nd Intl. Workshop Graph-Based Tools (GraBaTs'04). Elsevier ENTCS 127(1):113-125, 2005.

• Ulrik Brandes and Jürgen Lerner: Structural Similarity in Graphs. Proc. 15th Intl. Symp. Algorithms and Computation (ISAAC'04). Springer LNCS, pp. 184-195. Springer-Verlag, 2004.

• Michael Baur, Marc Benkert, Ulrik Brandes, Sabine Cornelsen, Marco Gaertler, Boris Köpf, Jürgen Lerner, and Dorothea Wagner: visone - Software for Visual Social Network Analysis. Proc. 9th Intl. Symp. Graph Drawing (GD'01), LNCS 2265, pp.463-464. Springer-Verlag, 2002.

Editorial

• Jürgen Lerner, Dorothea Wagner, and Katharina A. Zweig (Eds.): Algorithmics of Large and Complex Networks. LNCS, vol. 5515. Springer-Verlag, 2009.

Book chapters

• Jürgen Lerner: Beziehungsmatrix. In: Stegbauer, C., Häußling, R. (eds) Handbuch Netzwerkforschung, 2nd edition. Springer VS, Wiesbaden, 2023. DOI: https://doi.org/10.1007/978-3-658-37507-2_32-1

• Patrick Kenis and Jürgen Lerner: Wikipedia Collaborative Networks. In: Encyclopedia of Social Network Analysis and Mining, 2nd edition. Springer New York, 2017.

• Jose Luis Molina, Jürgen Lerner, Miranda J. Lubbers, and Aurelio Díaz: Transnacionalismo, negocios étnicos y crisis económica en Cataluña. In: Magdalena Barros and Hugo Valenzuela (eds.) Retos y estrategias del empresariado étnico contemporáneo. CIESAS, 49-67, 2013.

• Ulrik Brandes, Markus Eiglsperger, Jürgen Lerner, and Christian Pich: GraphML. In: Roberto Tamassia (ed.) Handbook of Graph Drawing and Visualization, pp. 517-541. CRC Press, 2013. 

• Jürgen Lerner, Ulrik Brandes, Patrick Kenis, and Denise van Raaij: Modeling Open, Web-based Collaboration Networks: The Case of Wikipedia. In Markus Gamper, Linda Reschke, Michael Schönhuth (Eds.): Knoten und Kanten 2.0, pp 141-162. transcript-Verlag, 2012.

• Jürgen Lerner: Beziehungsmatrix. In Christian Stegbauer and Roger Häußling (Hrsg.): Handbuch Netzwerkforschung pp 355-364. VS Verlag, 2010.

• Michael Baur, Ulrik Brandes, Jürgen Lerner, and Dorothea Wagner: Group-Level Analysis and Visualization of Social Networks. In Jürgen Lerner, Dorothea Wagner, and Katharina A. Zweig (Eds.): Algorithmics of Large and Complex Networks. LNCS, vol. 5515, pp 330-358. Springer-Verlag, 2009.

• Ulrik Brandes and Jürgen Lerner: Visualization of Conflict Networks, (access to PDF). In Mayeul Kauffmann (Ed.): Building and Using Datasets on Armed Conflicts, NATO Science for Peace and Security Series E: Human and Societal Dynamics - Vol. 36, pp. 169-188. IOS Press, 2008. 

• Jürgen Lerner: Role Assignments. In: Ulrik Brandes and Thomas Erlebach (Eds.): Network Analysis: Methodological Foundations. LNCS Tutorial, vol. 3418, pp 216-252. Springer-Verlag, 2005.

• other (not peer-reviewed)

• Jürgen Lerner, Mark Tranmer, John Mowbray, and Marian-Gabriel Hancean: REM beyond dyads: relational hyperevent models for multi-actor interaction networks. arXiv preprint arXiv:1912.07403, 2019.

• The visone development team: visone wiki - tutorials for the visone software. 

• Ulrik Brandes, Markus Eiglsperger, and Jürgen Lerner: GraphML Primer - an easy introduction to GraphML.