ivymoruri-coder/Kenya-Sentiment-Analysis

Sentiment analysis of Kenyan tweets using machine learning and natural language processing (NLP). # Kenya-Sentiment-Analysis Sentiment analysis of Kenyan tweets using machine learning and natural language processing (NLP). This project focuses on sentiment analysis of Kenyan tweets using XLM-R (XLM-RoBERTa), a state-of-the-art multilingual transformer model. The goal is to automatically determine whether a tweet expresses a positive, negative, or neutral sentiment. The workflow includes data preprocessing (cleaning and normalizing tweets), feature extraction with XLM-R embeddings, and training sentiment classifiers to evaluate model performance. By leveraging XLM-R, the project is able to handle multilingual and low-resource languages such as Swahili, Sheng, and English, which are common in Kenyan social media conversations. This project can serve as a foundation for applications in social media monitoring, opinion mining, and policy analysis, offering insights into public sentiment around topics relevant to Kenya.