An assessment of the role of big data in computational linguistics for Efik language preservation
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Background of the Study
Big data analytics has transformed the landscape of computational linguistics by enabling the processing of vast and diverse datasets. For the Efik language, spoken in Cross River State, the integration of big data approaches offers unprecedented opportunities for language preservation and revitalization. Large-scale digital corpora, gathered from social media, literature, and historical documents, provide comprehensive linguistic data that can be analyzed using advanced computational tools (Mbanefo, 2023). These tools facilitate the identification of linguistic patterns, evolution in syntax and semantics, and cultural expressions embedded in Efik texts. Big data allows researchers to uncover hidden trends and make data-driven decisions to enhance language education, digital archiving, and cultural heritage projects (Edet, 2024). Furthermore, leveraging big data in computational linguistics can help overcome the limitations posed by small, fragmented datasets, ensuring that the rich nuances of the Efik language are accurately captured and preserved (Akanbi, 2025). This study investigates how big data methodologies are being applied to Efik language research and examines their effectiveness in supporting comprehensive language preservation efforts.
Statement of the Problem
Although big data offers vast potential for computational linguistics, the Efik language remains underrepresented in large-scale digital datasets. The scarcity of comprehensive and well-annotated corpora limits the ability of researchers to fully leverage big data techniques for language preservation (Mbanefo, 2023; Edet, 2024). Inadequate data collection and processing infrastructures further impede the development of robust computational models tailored for Efik. These shortcomings hinder efforts to document, analyze, and revitalize the language, creating a gap between technological capabilities and cultural preservation needs. Therefore, a systematic assessment is required to evaluate the role of big data in computational linguistics for Efik and to propose strategies for enhancing data collection and processing.
Objectives of the Study
- To assess the availability and quality of big data resources for Efik language research.
- To evaluate the effectiveness of big data techniques in computational linguistics for Efik preservation.
- To recommend strategies to improve data collection and analysis for Efik language revitalization.
Research Questions
- What is the current state of big data resources available for Efik language research?
- How effective are big data techniques in analyzing Efik linguistic features?
- What improvements can be made to enhance big data applications in Efik preservation?
Significance of the Study
This study is significant as it explores the transformative potential of big data in preserving the Efik language. By evaluating current methodologies and identifying data gaps, the research provides actionable insights for linguists, cultural preservationists, and technologists. The findings will support enhanced digital archiving, language revitalization, and policy development, ensuring that Efik’s linguistic heritage is preserved for future generations.
Scope and Limitations of the Study
This study focuses on the role of big data in computational linguistics for Efik language preservation. It does not extend to other languages or unrelated computational methods.
Definitions of Terms
- Big Data: Extremely large datasets that can be analyzed computationally to reveal patterns and trends.
- Computational Linguistics: The use of computer algorithms to analyze and model natural language.
- Language Preservation: Efforts to maintain and revitalize endangered or under-resourced languages.
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