Storylines with a Protagonist

Authors Tim Hegemann , Alexander Wolff



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Author Details

Tim Hegemann
  • Universität Würzburg, Germany
Alexander Wolff
  • Universität Würzburg, Germany

Acknowledgements

We thank Felix Klesen for many discussions and Tim Herrmann for implementing the first version of GreedyBlocks. We also thank the reviewers of this paper for many helpful comments.

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Tim Hegemann and Alexander Wolff. Storylines with a Protagonist. In 32nd International Symposium on Graph Drawing and Network Visualization (GD 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 320, pp. 26:1-26:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.GD.2024.26

Abstract

Storyline visualizations show interactions between a given set of characters over time. Each character is represented by an x-monotone curve. A meeting is represented by a vertical bar that is crossed by the curves of exactly those characters that participate in the meeting. Therefore, character curves may have to cross each other. In the context of publication networks, we consider storylines where the characters are authors and the meetings are joint publications. We are especially interested in visualizing a group of colleagues centered around an author, the protagonist, who participates in all selected publications. For such instances, we propose a drawing style where the protagonist’s curve is drawn at a prominent position and never crossed by any other author’s curve. We consider two variants of storylines with a protagonist. In the one-sided variant, the protagonist is required to be drawn at the top position. In this restricted setting, we can efficiently compute a drawing with the minimum number of pairwise crossings, whereas we show that it is NP-hard to minimize the number of block crossings (i.e., pairs of blocks of parallel curves that intersect each other). In the two-sided variant, the task is to split the set of co-authors of the protagonist into two groups, and to place the curves of one group above and the curves of the other group below the protagonist’s curve such that the total number of (block) crossings is minimized. As our main result, we present an algorithm for bundling a sequence of pairwise crossings into a sequence of few block crossings (in the absence of meetings). It exploits a connection to a rectangle dissection problem. In the presence of meetings, it yields results that are very close to a lower bound. Based on this bundling algorithm and our exact algorithm for the one-sided variant, we present a new heuristic for computing two-sided storylines with few block crossings. We perform an extensive experimental study using publication data of 81 protagonists from GD 2023 and their most frequent collaborators over the last ten years. Our study shows that, for two-sided storylines with a protagonist, our new heuristic uses fewer block crossings (and fewer pairwise crossings) than two heuristics for block crossing minimization in general storylines.

Subject Classification

ACM Subject Classification
  • Theory of computation → Graph algorithms analysis
  • Human-centered computing → Graph drawings
Keywords
  • Storyline visualization
  • storyline with a protagonist
  • crossing minimization
  • block crossings

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