About My Project
Project Title
The African Diaspora Media Hub
Problem
Despite the vast and diverse media content generated across the African Diaspora, there is a lack of centralized platforms that effectively curate, analyze, and personalize this content for educational, cultural, and social engagement. Existing media hubs often overlook nuanced representations of Black identities and fail to support multilingual accessibility across African and diaspora languages. This fragmentation limits the visibility of underrepresented voices, hinders academic research, and reduces user engagement. There is a need for an intelligent, inclusive platform that leverages AI and machine learning to organize, interpret, and amplify content related to the African Diaspora in a meaningful and accessible way.
Approach
The project follows a four-phase pipeline:
- Aggregate news, podcasts, videos, and social media content related to the African Diaspora using web scraping tools and APIs.
- Use Natural Language Processing (NLP) techniques to organize and tag media content by theme, sentiment, region, and relevance to Black identity and representation.
- Train machine learning models for sentiment analysis, content recommendation, transcription, and multilingual translation to enhance accessibility and personalization.
- Conduct user testing and feedback collection to refine user experience, ensure content accuracy, and improve the system’s performance.
Open-source tools such as Python (with libraries like NLTK, TensorFlow, and Flask), Hugging Face for NLP models, and React for front-end development will be used to prototype the platform.
Expected Outcome
This project will result in a working digital media hub that highlights African diaspora narratives with AI-driven features. It will support multilingual access and offer a user-friendly interface, while giving researchers practical experience in AI, media analysis, and platform development.
Final Report: View PDF