A framework for the adoption of social media in crime investigations: case of Uganda Police in Kampala Metropolitan Area

Abstract

The exponential rise of social media platforms presents unique opportunities for enhancing crime investigation efforts within law enforcement agencies. This study investigates the integration of social media into crime investigation processes within the Uganda Police Force (UPF), focusing on the Kampala Metropolitan Area. Despite technological advancements and increased smartphone usage, the UPF has faced significant challenges in leveraging digital tools for timely evidence gathering, suspect identification, and digital forensics. This research aimed to develop a practical framework to guide the adoption and use of social media in crime investigations. Using a Design Science Research (DSR) methodology complemented by an abductive research approach, the study collected primary data through structured questionnaires distributed to police personnel and analysed it using statistical tools. It further reviewed existing global frameworks and theoretical models such as the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Crime Pattern Theory to inform framework development. Findings indicated that perceived usefulness, ease of use, organizational support, training, and investigative protocols significantly affect social media adoption for crime investigations. The final framework was structured in three phases: pre-adoption, adoption, and post-adoption, each addressing specific functional, organizational, and technical requirements for digital investigation. The framework was validated through expert reviews and statistical analysis, demonstrating its potential to improve digital evidence collection, suspect identification, witness location, and investigative efficiency. The study contributes to both academic research and practical implementation by offering a structured, context-specific model that can be adapted by law enforcement agencies across similar settings.