Graph-Drawing Supported Identification of Influential Students at Schools (Poster Abstract)

Authors Markus Chimani , Lea Kröger, Juliane Liedtke, Jonah Mevert, Maor Shani , Maarten van Zalk



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Author Details

Markus Chimani
  • Theoretical Computer Science, Osnabrück University, Germany
Lea Kröger
  • Theoretical Computer Science, Osnabrück University, Germany
Juliane Liedtke
  • VNB (Association of Education Initiatives in Lower Saxony), Hannover, Germany
Jonah Mevert
  • Theoretical Computer Science, Osnabrück University, Germany
Maor Shani
  • Developmental Psychology, Osnabrück University, Germany
Maarten van Zalk
  • Developmental Psychology, Osnabrück University, Germany

Cite AsGet BibTex

Markus Chimani, Lea Kröger, Juliane Liedtke, Jonah Mevert, Maor Shani, and Maarten van Zalk. Graph-Drawing Supported Identification of Influential Students at Schools (Poster Abstract). In 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 320, pp. 44:1-44:3, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.GD.2024.44

Abstract

We consider the real-world problem of identifying a set of "influential" students at schools for a workshop on tolerance. We report on a tool that visualizes the networks of social connections between students, identifies sets of influential students, and lets one explore and understand the solution space with a focus on usability for teachers who are untrained in network analysis.

Subject Classification

ACM Subject Classification
  • Applied computing → Law, social and behavioral sciences
Keywords
  • social network tool
  • force-directed graph drawing
  • group centrality

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References

  1. Markus Chimani, Carsten Gutwenger, Michael Jünger, Gunnar W. Klau, Karsten Klein, and Petra Mutzel. The open graph drawing framework (OGDF). In Roberto Tamassia, editor, Handbook of Graph Drawing and Visualization, chapter 17. CRC press, 2014. See URL: www.ogdf.net.
  2. Robin Gomila, Hana Shepherd, and Elizabeth L. Paluck. Network insiders and observers: who can identify influential people? Behavioural Public Policy, 7(1):115-142, 2023. Google Scholar
  3. Stefan Hachul and Michael Jünger. Drawing large graphs with a potential-field-based multilevel algorithm. In Janos Pach, editor, Proc. Graph Drawing 2004, volume 3383 of LNCS, pages 285-295. Springer-Verlag, 2004. URL: https://doi.org/10.1007/978-3-540-31843-9_29.
  4. Elizabeth L. Paluck and Hana Shepherd. The salience of social referents: a field experiment on collective norms and harassment behavior in a school social network. Journal of Personality and Social Psychology, 103(6):899-915, 2012. Google Scholar
  5. Maor Shani, Sophie de Lede, Stefanie Richters, Malin Kleuker, Wilma Middendorf, Juliane Liedtke, Sandrine Witolla, and Maarten van Zalk. A social network intervention to improve adolescents’ intergroup tolerance via norms of equality-based respect: the “together for tolerance” feasibility study. International Journal of Developmental Science, 17(1-3):93-110, 2023. Google Scholar
  6. Maarten van Zalk, Oliver Christ, Eva Jaspers, Miranda J. Lubbers, Marcin Bukowski, Maor Shani, Laura F. Schäfer, Alejandro Ciordia, Anna Potoczek, Jan-Willem Simons, Nina Tegeler, Lucía Estevan-Reina, and Wilma Middendorf. Inclusivity norms to counter polarization in european societies (inclusivity), 2023. Project description. URL: https://osf.io/n7c4y/.
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