Language Resource Acquisition for Low-Resource Languages in Digital Discourses

Abstract

This chapter explores the acquisition of language resources for low-resource languages in digital discourse, focusing on code-mixed content in social media posts and comments. Comprehensive language resources enhance our understanding of language usage patterns in online discussions. The methodology includes data collection, annotation, and automated tools, resulting in a practical framework. Challenges addressed in the chapter include data diversity, annotation complexity, linguistic variability, limited annotated data, and ethical considerations. Solutions proposed range from robust data preprocessing techniques to contextual analysis approaches, ensuring acquired quality and ethical use of resources. The chapter also discusses future directions, paving the way for further research and technology development in natural language processing and sociolinguistics. This chapter equips researchers and practitioners with essential knowledge and tools for advancing linguistic analysis and technological applications in the evolving digital landscape.