Digital Classic Grounded Theory

Classic GT (Glaserian) demands strict inductive emergence and discourages literature engagement until the core category is identified; it operates from a realist epistemology. Straussian GT (Strauss and Corbin) introduces more structured coding procedures (open, axial, selective) and is more tolerant of prior concepts. Constructivist GT (Charmaz) foregrounds the researcher's role in constructing categories and adopts a relativist or interpretivist stance. In the digital context, all three can handle online data, but the analytic logic and epistemological commitments differ significantly.

This is genuinely contested. Many ethical frameworks distinguish between data posted in clearly public spaces (e.g., public Twitter/X accounts) and data posted in semi-public or community spaces (e.g., support groups that are technically public but normatively private). The Association of Internet Researchers (AoIR) ethics guidelines recommend case-by-case assessment based on context, sensitivity of topic, and the reasonable expectations of community members. Always consult your institution's ethics board.

Saturation is reached when additional theoretical sampling — deliberately seeking new digital contexts, time periods, or participant types to test and elaborate your categories — no longer generates new conceptual properties or variations. It is a conceptual judgment, not a count of posts. Thorough memoisation is essential for recognising saturation, because it lets you track what each new incident added to the developing theory.

Classic GT does not require triangulation as a validation strategy — it validates through the theoretical logic of the emerging theory itself. However, for phenomena where naturally occurring digital text is thin or ambiguous, supplementing with online interviews or observational fieldwork (lurking, shadowing) can enrich the data. The decision should be driven by the requirements of theoretical sampling, not by a default assumption that mixed data are always better.

Yes, but with caution. Software can manage and organise large volumes of digital text and support coding. However, the intellectual work — inducing concepts, writing memos, identifying the core category — cannot be automated. Glaser himself expressed scepticism about software, fearing it encourages mechanical coding at the expense of theoretical thinking. Use it as a filing and retrieval tool, not as an analytic engine.