Mbashaliee/NaijFactCheck-AI

Fake News Detection in Local Nigerian Languages (Hausa, Yoruba, Igbo, Pidgin) # 📰 NaijFactCheck AI - Fake News Detection in Local Languages ## 🚀 Project Overview This project aims to build an **AI & ML powered system** that detects fake news articles, social media posts, and online content in **local Nigerian languages** (Hausa, Yoruba, Igbo). The goal is to curb misinformation that spreads quickly in local communities and affects politics, health, and security. ## 📌 Problem Fake news is a global challenge, but in Nigeria, the issue is amplified due to: - Low digital literacy rates (UNESCO reports Nigeria has ~40% digital illiteracy). - Widespread use of **local languages** in rural areas where misinformation spreads unchecked. - Studies show that during elections, **over 50% of viral WhatsApp messages were misleading**. - COVID-19 fake news in Hausa led to vaccine resistance in Northern Nigeria. ## 💡 Solution We propose a **multilingual fake news detection system** that: - Collects and processes text in **Hausa, Yoruba, and Igbo**. - Uses **NLP (Natural Language Processing)** with **machine learning models** to classify news as **real or fake**. - Provides a simple web/app interface for users to test the credibility of texts. - Can be extended to WhatsApp/Facebook monitoring in the future. ## ⚙️ Tech Stack - **Python** (NLTK, Hugging Face Transformers, scikit-learn, TensorFlow/PyTorch) - **Data**: Web scraped Nigerian news (BBC Hausa, Premium Times, Punch, etc.) - **Deployment**: Streamlit / Flask for demo - **Languages**: Hausa, Yoruba, Igbo + English baseline ## 📊 Challenges - Lack of large labeled datasets in local languages. - Translating and pre-processing mixed-language (code-switching) text. - Building lightweight models that can run on low-resource devices. ## 🛠️ Progress - [ ] Data collection (news articles & social media posts) - [ ] Text preprocessing & language translation - [ ] Model training (Baseline: Logistic Regression, Advanced: BERT-based models) - [ ] Evaluation & demo app ## 👥 Team Currently: **1 member (open to c …