Applying Sentiment Analysis on Children’s Stories

Today in the world, the rapid and widespread adoption of modern technologies has changed the way that we can access information from news, conversations, and exchange of views about any topics that could attract people's attention. Current communication on the Internet allows people in the community to present and share their ideas in publications and interact with others on different subjects. These data contain a large amount of common knowledge that can be used in scientific and humanitarian research to generalize the benefit to all people everywhere. With the advancement of artificial intelligence and its branches and by using these data, we can solve the various problems that face us in life. Natural language processing is one of the most important issues that have arisen in parallel with the developments of artificial intelligence. Sentiment analysis is regarded as a computational technique that aids in determining and evaluating people's emotions through written documents. Therefore, in this study, we will focus on the sentiment analysis by applying Random Forest and Decision Tree algorithms on the dataset containing children’s stories. The results showed that the accuracy rate attained by Random Forest was 98.32% while Decision Tree gave 97.74%.