Chapters authored
Using Sentiment Analysis and Machine Learning Algorithms to Determine Citizens’ Perceptions
This chapter analyzes the opinions expressed by individuals on four topical Jamaican issues and classifies them by emotions, feelings and polarity. The four trending topics on Twitter analyzed are the decriminalization of marijuana in Jamaica, Kaci Fennell’s placing in Miss Universe, the Riverton Landfill fire and Barack Obama’s working visit to Jamaica. The data pulled from Twitter for each topic was mined using three different classification algorithms to identify the accuracy of the data classified based on the polarity. The classifiers identified which polarity reflected what opinion is more dominant of the three; which are negative, positive or neutral. Sentiment analysis tools classified the opinions of Jamaican Twitter users with over 70% accuracy. Among three classification algorithms used, J48 decision tree received highest accuracy for the four topics tested and maintained the lowest error rate. For the decriminalization of marijuana, Kaci Fennell’s placing in the Miss Universe competition and President Obama’s visit, the accuracy was just over 70% and the mean absolute error (MAE) was less than 0.3. The methodology of the study provides a blueprint which can be utilized by managers and other decision making stakeholders to determine consumers’ perception.
Part of the book: Machine Learning