Ensuring Accuracy in AI-Driven Image Sentiment Analysis: A Functional Testing Approach

The rapid advancement of Artificial Intelligence (AI) in image recognition and sentiment analysis has introduced new challenges in functional testing. This paper explores the methodologies used to validate AI-generated sentiment analysis on images. It details the challenges encountered, testing strategies, step-by-step functional testing processes, and best practices to ensure the accuracy and reliability of the AI model. This white paper can be effectively used by QA teams, developers, and product owners to select the most appropriate image sentiment analysis tool by comparing accuracy, performance, and reliability. It also serves as a reference framework to build or enhance functional testing strategies for AI-based image sentiment systems, guiding both manual and automated test planning.