A novel, human-in-the-loop computational grounded theory framework for big social data
The availability of big data has significantly influenced the possibilities and methodological choices for conducting large-scale behavioural and social science research. In the context of qualitative data analysis, a major challenge is that conventional methods require intensive manual labour and a...
Saved in:
| Main Authors: | Lama Alqazlan, Zheng Fang, Michael Castelle, Rob Procter |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-06-01
|
| Series: | Big Data & Society |
| Online Access: | https://doi.org/10.1177/20539517251347598 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Survey of Distributed Computing Frameworks for Supporting Big Data Analysis
by: Xudong Sun, et al.
Published: (2023-06-01) -
SPARC: A Human-in-the-Loop Framework for Learning and Explaining Spatial Concepts
by: Brendan Young, et al.
Published: (2025-03-01) -
Using Grounded Theory
by: Michael Thomas
Published: (2025-06-01) -
MITSGRN: A Novel Computational Framework for Reconstructing Sleep Rhythm Gene Regulatory Networks Based on Mutual Information and Time-Series Big Data
by: Zhenyu Liu, et al.
Published: (2025-01-01) -
When is Grounded Theory (GT) Not Grounded Theory
by: Barry Chametzky
Published: (2025-06-01)