The Rich Facets of Digital Trace Data

Jonas Valbjørn Andersen, Philipp Hukal

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review


Increasing digitalization means that many of our daily interactions happen within digital environments where they leave digital footprints in the form of trace data. Such digital trace data is often thought to generate insights by virtue of its immense scale. This focus on ‘big data’ tends to overlook the richness and complex characteristics of digital traces that opens new vistas for a multitude of computational analyses that generate new and high-resolution insights to digital environments. As such, paying attention to the characteristics of trace data allows for deep investigations of social-technical interactions in unprecedented detail.

This chapter describes the process of digital trace analysis through four analytical activities aimed at identifying units of analysis, extracting categories, validating patterns and conceptualizing findings from digital trace data. It then shows how analytical activities can be applied to a given digital trace dataset to derive three ‘facets’ that each provide rich conceptualizations of social interaction with technology. It explains each facet and outlines ways to implement digital trace analyses that focus on facets relating to relations (network analysis), processes (sequence analysis) or semantics (text analysis).
Original languageEnglish
Title of host publicationCambridge Handbook of Qualitative Digital Research
EditorsBoyka Simeonova, Robert D. Galliers
Number of pages21
Place of PublicationCambridge
PublisherCambridge University Press
Publication date2023
ISBN (Print)9781009098878
ISBN (Electronic)9781009106436
Publication statusPublished - 2023


  • Digital trace data
  • Computational social science
  • Computational qualitative analysis
  • Network analysis
  • Topic modelling
  • Sequence analysis

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