Design Issues in Sentiment Analysis for Yorùbá Written Text

Abstract

Abstract. Sentiment Analysis (SA) is an exciting and important field in Artificial Intelligence combining Human Language Processing, Machine Learning and Psychology. It is a means of understanding a user’s opinion about an event. The goal of SA is to get opinion expressed in implied text, targets of the opinion and reason for the opinion. Conversely, a great number of research efforts are dedicated to English language data, while a countless share of information is obtainable in other languages as well but none yet for Yorùbá. This work examines the design issues with respect to automating SA for standard Yorùbá language. The process of SA which includes data cleaning, data annotation etc. is highlighted. The structure of the Yorùbá text is described and a text corpus design for Yorùbá sentiment analysis system is presented. The outcome of this work provided suitable requirements for the design.