Selective Coding: Building the Core Story

Big Data: We generate enormous amounts of data (social media, sensors, transactions) that AI can learn from.
Computing Power: Modern GPUs perform trillions of calculations per second, making AI training feasible.
Better Algorithms: The Transformer architecture (2017) unlocked capabilities previously impossible.

The final stage identifies a central, unifying category that the other categories relate to — the core narrative or theoretical account that ties the analysis together, especially central to grounded theory.

Deductive vs. Inductive Coding

Deductive	Inductive
Codes come from existing theory or a predetermined framework	Codes emerge directly from the data itself
Faster, more structured, tests existing ideas	Slower, more exploratory, can surface unexpected findings

Many studies use a hybrid approach: starting with a small set of deductive codes from theory or research questions, while remaining open to new inductive codes the data suggests.

Using Qualitative Data Analysis Software

Tools like NVivo, ATLAS.ti, and MAXQDA (or even a well-organized spreadsheet for smaller projects) help manage large volumes of coded data, track code frequency, and visualize relationships — but the software does not do the actual intellectual work of coding; that remains the researcher's judgment.

Tutorials & Deep Dives