ANALYSIS OF PUBLIC REACTION TO E-LEARNING ON TWITTER

Abstract

Over the past few decades, due to the explosive growth of social media, online resources, and microblogging sites such as Twitter. There was an influx of user-generated content. The data obtained from these resources is a rich source of information for data mining. Sentiment analysis is a current and important area of research that attempts to determine the polarity of a text. The definition of feelings about current events in the world has become crucial. This article focuses on data mining on Twitter and defining opinions regarding e-learning. The focus is on identifying sentiment from e-learning-related texts that are shared on Twitter. About 3,000 tweets were extracted and the polarity of those tweets was detected, and then visualize the resulting data.