Sentiment Analysis to Measure Celebrity Endorsment’s Effect using Support Vector Machine Algorithm

Abstract

Celebrity endorsement is a phenomenon in which companies advertises their products by using celebrity services, and celebrities take advantage of their popularity to promote a brand or product of the company through social media. In this study, KFC did a celebrity endorsement to make their menu more popular. KFC choose to work with Raditya Dika to promote their latest menu, KFC Salted Egg Chicken. This study will examine whether in such cases there is a change in public sentiment towards the product after the celebrity endorsement. It can be done using text mining and sentiment analysis. There are several algorithms that can be used to perform sentiment analysis, one of them is Support Vector Machine. Support Vector Machine (SVM) was chosen because this method is quite accurate in various studies. SVM also takes into account various features of the document, including features that often do not appear on the document, so it can reduce the loss of information from the data. The data used in this research are taken from YouTube and Twitter comment about KFC Salted Egg Chicken. Several step was done in this sentiment analysis research, that are preprocessing text, feature extraction, classification, and evaluation. The result model is tested and evaluated before and after endorsement by looking at the value of accuracy, precision, recall, and f1-measure. The test result of accuracy, precision, recall, and f-measure before endorsement were 67,83%, 69%, 68%, and 66%. After the endorsement, the test results were 74.06%, 74%, 74%, and 74% respectively. The results of this study indicate that SVM has an accurate measurement in sentiment analysis studies. Moreover, this study found that there was not significant change in public sentiment regarding the product before and after the celebrity endorsement.