An investigation of computational semantic analysis in Nigerian Pidgin social media discourse
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- NGN 5000
Background of the Study
Computational semantic analysis has emerged as an essential tool for understanding the meaning behind online discourse. In Nigerian Pidgin social media, users express ideas, emotions, and cultural nuances in a dynamic and informal language. Semantic analysis techniques—such as word embeddings, topic modeling, and sentiment analysis—are applied to extract meaningful patterns and gauge public opinion (Udo, 2023). Given the rapid evolution of Nigerian Pidgin and its frequent code-switching with other languages, computational methods must adapt to non-standard grammar and novel expressions. Researchers have employed advanced neural network models and contextual analysis to better capture semantic shifts in social media conversations (Chukwuemeka, 2024). These techniques provide insights into how language reflects societal trends, cultural identity, and social attitudes. However, challenges remain due to the informal and fluid nature of online communication. Continuous refinement of semantic analysis algorithms is required to accurately interpret the diverse expressions found in Nigerian Pidgin discourse (Nnamdi, 2025). This study investigates the effectiveness of current computational semantic analysis methods and explores enhancements that can address the unique characteristics of Nigerian Pidgin on social media platforms.
Statement of the Problem
Despite the potential of computational semantic analysis, existing methods struggle to accurately interpret Nigerian Pidgin social media discourse. The language’s informal nature, frequent code-switching, and rapidly evolving vocabulary result in misinterpretation of context and sentiment (Udo, 2023; Chukwuemeka, 2024). These challenges hinder reliable analysis of public opinion and cultural trends, limiting the utility of automated semantic tools for research and policy formulation. Addressing these limitations is essential for developing robust semantic analysis models.
Objectives of the Study
- To evaluate current computational semantic analysis techniques applied to Nigerian Pidgin social media.
- To identify challenges in capturing the nuances of informal and evolving language use.
- To propose improvements for enhancing semantic analysis accuracy in Nigerian Pidgin.
Research Questions
- How effective are current semantic analysis methods in interpreting Nigerian Pidgin social media discourse?
- What challenges affect the accuracy of semantic interpretation in Nigerian Pidgin?
- How can computational semantic models be improved to better handle the language’s unique features?
Significance of the Study
This study is significant as it advances understanding of computational semantic analysis in Nigerian Pidgin, providing insights into improving automated discourse analysis. Its findings will benefit linguists, data scientists, and policymakers by enhancing tools that capture cultural nuances and inform social research, thus supporting better digital communication strategies.
Scope and Limitations of the Study
This study focuses on computational semantic analysis in Nigerian Pidgin social media discourse and does not extend to other languages or offline communication.
Definitions of Terms
- Semantic Analysis: The process of interpreting meaning from text data.
- Computational Linguistics: The use of computational methods to analyze language.
- Nigerian Pidgin: A creole language widely used in informal digital communications in Nigeria.
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