AFRICAN JOURNAL OF COMMUNICATION AND LANGUAGE

This study evaluated Cultural Contact, Identity Friction and Intergroup Relations between Igbo and Ikwere Communities. The research sought to investigate historical and cultural dynamics shaping communication, identify factors that enhance effective intercultural communication, and examine challenges and opportunities for fostering social cohesion between the two communities. Guided by Cross-Cultural Communication Theory and Social Identity Theory, the study adopted a triangulation research design, combining surveys and focus group discussions. The population consisted of approximately 1,005,904 residents of Port Harcourt and Obio-Akpor Local Government Areas, with a sample of 400 respondents selected using purposive and availability sampling techniques, focusing on knowledgeable community members such as elders, chiefs, and leaders. Data were collected using a structured questionnaire and interview guide, validated by experts, and reliability tested via Cronbach’s Alpha. Analysis employed descriptive statistics, weighted means, and standard deviations. Findings revealed that historical events, migration patterns, and cultural traditions significantly influence communication between the Igbo and Ikwerre communities. Factors such as shared language, mutual respect, participation in community activities, and cultural awareness were identified as critical in promoting effective crosscultural communication. Conversely, stereotypes, differing communication styles, historical grievances, and limited cultural knowledge were found to hinder understanding. The study also demonstrated that cross-cultural communication positively impacts interpersonal relations, fostering trust, cooperation, and social cohesion, while traditional and social media play a pivotal role in shaping cultural perceptions, identity expression, and intergroup attitudes. The study concludes that promoting cultural awareness, responsible media use, and inclusive engagement strategies is essential for strengthening Igbo–Ikwerre relations and enhancing social harmony. The findings provide actionable insights for policymakers, educators, and community leaders aiming to foster sustainable intercultural communication and cooperation in Nigeria.

This study investigates the role of data structures as a fundamental organising factor in the design of software and algorithms, with particular emphasis on their influence on computational efficiency, scalability, and system performance. Grounded in algorithmic complexity theory and data abstraction principles, the research adopts a computational experimental methodology that integrates theoretical analysis with empirical benchmarking. Specifically, commonly used data structures—arrays, linked lists, binary search trees, and hash tables were implemented and evaluated across core operations such as searching, insertion, deletion, and traversal under varying dataset sizes and workload conditions . The analytical framework combined Big-O complexity evaluation with real- time performance metrics, including execution time and memory utilisation, using programming environments such as Python and C++. The results reveal that data structure selection has a significant and measurable impact on algorithm efficiency. Hash tables consistently demonstrated superior performance in search operations with near- constant time complexity, while linked lists exhibited optimal efficiency in insertion and deletion tasks. Arrays, although simple in structure, showed notable performance degradation under large datasets due to linear time complexity, whereas binary search trees provided balanced performance contingent on structural conditions. Furthermore, performance disparities became more pronounced as computational workloads increased, highlighting the critical role of scalability in data structure selection. The study concludes that no single data structure is universally optimal; rather, performance is context-dependent and closely aligned with operational requirements and workload characteristics. Consequently, it is recommended that software developers adopt a context-sensitive and evidence-based approach to data structure selection, incorporating both theoretical complexity analysis and empirical testing. This approach is essential for developing efficient, scalable, and high-performance software systems.