![[2602.21217] Applied Sociolinguistic AI for Community Development (ASA-CD): A New Scientific Paradigm for Linguistically-Grounded Social Intervention](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
[2602.21217] Applied Sociolinguistic AI for Community Development (ASA-CD): A New Scientific Paradigm for Linguistically-Grounded Social Intervention
Summary
The paper introduces Applied Sociolinguistic AI for Community Development (ASA-CD), a paradigm that leverages AI and linguistics to address community challenges through structured social interventions.
Why It Matters
ASA-CD represents a significant advancement in using AI for social good, providing a framework for understanding and mitigating the impact of exclusionary language. This approach is crucial for fostering community empowerment and addressing social issues through linguistically-informed interventions.
Key Takeaways
- Introduces linguistic biomarkers as indicators of social fragmentation.
- Presents a development-aligned NLP approach prioritizing collective outcomes.
- Outlines a five-phase protocol for effective discursive intervention.
- Demonstrates the relationship between exclusionary language and negative sentiment.
- Provides a framework for scalable, ethical AI applications in community development.
Computer Science > Computation and Language arXiv:2602.21217 (cs) [Submitted on 30 Jan 2026] Title:Applied Sociolinguistic AI for Community Development (ASA-CD): A New Scientific Paradigm for Linguistically-Grounded Social Intervention Authors:S M Ruhul Alam, Rifa Ferzana View a PDF of the paper titled Applied Sociolinguistic AI for Community Development (ASA-CD): A New Scientific Paradigm for Linguistically-Grounded Social Intervention, by S M Ruhul Alam and Rifa Ferzana View PDF Abstract:This paper establishes Applied Sociolinguistic AI for Community Development (ASA-CD) as a novel scientific paradigm for addressing community challenges through linguistically grounded, AI-enabled intervention. ASA-CD introduces three key contributions: (1) linguistic biomarkers as computational indicators of discursive fragmentation; (2) development-aligned natural language processing (NLP), an AI optimisation paradigm prioritising collective outcomes; and (3) a standardised five-phase protocol for discursive intervention. A proof-of-concept study, incorporating real-world and synthetic corpora, demonstrates systematic associations between exclusionary language and negative sentiment and simulates intervention-based improvements. ASA-CD provides a unified methodological, ethical and empirical framework for scalable, value-aligned AI in the service of community empowerment. Comments: Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Computers and Society (cs.CY)...
