shaafi56/-Classifying-Somali-News-into-International-and-Local-Categories-using-NLP-Text-Classification

we developed algorithms that classify 600 Somali news into two distinct categories: International and Local. # -Classifying-Somali-News-into-International-and-Local-Categories-using-NLP-Text-Classification we developed algorithms that classify 600 Somali news into two distinct categories: International and Local. INTRODUCTION In our study titled "Navigating the News Landscape: Classifying Somali News into International and Local Categories using a Supervised Text Classification Approach," we developed algorithms that classify 600 Somali news into two distinct categories: International and Local. These algorithms analyze the content of each news piece and determine whether it pertains to global events or local Somali happenings. This categorization simplifies the process of finding relevant news for readers and provides insights into the types of stories covered in Somali news. Our approach showcases the practical application of machine learning in organizing and understanding news content. OVERVIEW As students, we've successfully developed a Python script for classifying Somali news articles. This script highlights our skills in data science and machine learning, incorporating various libraries for data handling, visualization, and natural language processing. Key components of our work include: Library Integration: Using pandas, matplotlib, WordCloud, nltk, and sklearn for diverse tasks ranging from data manipulation to text analysis.