Designing Analytical Pipelines in Digital Qualitative Sociology (Algorithmic Reflexivity and API-based Integration with LLMs)

Introduction
The increasing integration of application programming interfaces (APIs) with large language models (LLMs) is reshaping the methodological landscape of qualitative sociology. Traditional hermeneutic workflows foreground interpretive reflexivity and human-centered sense-making, whereas API-driven pipelines emphasize algorithmic reflexivity—a critical awareness of how computational infrastructures, design choices, and parameter settings shape sociological knowledge production.

Goals and Methods
This paper aims to conceptualize and demonstrate how analytical pipelines built on APIs can be designed and mobilized in digital qualitative research. Analytical pipelines automate complex chains of operations: from data collection and preprocessing through LLM-powered categorization and pattern detection to integration with visualization dashboards or network analysis platforms. The methodological design highlights modularity, extensibility, and scalability by orchestrating diverse tools, including computer-assisted qualitative data analysis software (CAQDAS), natural language processing libraries, and custom scripts. Practical demonstrations illustrate how API-based pipelines can be developed as cohesive architectures, enabling new methodological affordances in qualitative sociology.

Results
The expected outcomes show that API-based pipelines advance transparency and reproducibility while facilitating innovative combinations of interpretive and computational techniques. At the same time, they foreground algorithmic reflexivity, drawing attention to how infrastructures, model updates, and parameter adjustments co-produce analytical outcomes in new developing paradigm: Digital Qualitative Sociology. Rather than treating pipelines as neutral conduits, researchers must acknowledge them as socio-technical constructs embedding assumptions about language, meaning, and scale.

Conclusions
API-driven analytical pipelines constitute central infrastructures for qualitative sociology in the digital age. They expand methodological repertoires, enable scalable and transparent analysis, and support critical reflexivity at the intersection of human interpretation and computational mediation. However, they also raise challenges of interpretability, dependency, and ethical accountability. The paper concludes by positioning algorithmic reflexivity as a necessary complement to interpretive reflexivity, advancing both methodological innovation and critical awareness in digital qualitative research.