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Sense-making strategies in explorative intelligence analysis of network evolutions

Author

Listed:
  • Johanna Doppler Haider
  • Bettina Gastecker
  • Margit Pohl
  • Patrick Seidler
  • Neesha Kodagoda
  • B. L. William Wong

Abstract

Visualising how social networks evolve is important in intelligence analysis in order to detect and monitor issues, such as emerging crime patterns or rapidly growing groups of offenders. It remains an open research question how this type of information should be presented for visual exploration. To get a sense of how users work with different types of visualisations, we evaluate a matrix and a node-link diagram in a controlled thinking aloud study. We describe the sense-making strategies that users adopted during explorative and realistic tasks. Thereby, we focus on the user behaviour in switching between the two visualisations and propose a set of nine strategies. Based on a qualitative and quantitative content analysis we show which visualisation supports which strategy better. We find that the two visualisations clearly support intelligence tasks and that for some tasks the combined use is more advantageous than the use of an individual visualisation.

Suggested Citation

  • Johanna Doppler Haider & Bettina Gastecker & Margit Pohl & Patrick Seidler & Neesha Kodagoda & B. L. William Wong, 2019. "Sense-making strategies in explorative intelligence analysis of network evolutions," Behaviour and Information Technology, Taylor & Francis Journals, vol. 38(2), pages 198-215, February.
    • Handle: RePEc:taf:tbitxx:v:38:y:2019:i:2:p:198-215
    DOI: 10.1080/0144929X.2018.1519036
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