Sentiment Dynamics Detection of Online Learning Impact using Hybrid Approach

Abstract

With the growth of technology, the concept of online learning has grown in popularity. The worldwide epidemic situation (Covid 19) has increased the use of online learning not just in Higher Education Institutions (HEIs), but also at all levels of education (ISED levels). In these hard times, technical advancements have played a greater role in creating awareness of the existence of online learning which has evolved as an alternate avenue for gaining and disseminating knowledge in a systematic way.

In this paper we investigate to detect the sentiment dynamics (SD) of tweets related to online education available on twitter platform and deduce conclusions about its impact on student’s emotions. Over one lakh subjective tweets about the world's emerging online education system have been gathered via Twitter. Sentiment analysis was performed on the gathered dataset using the combination of dictionary-based and statistical-based approaches. Based on the findings of this analysis, we can infer the impact of online education and how people's attitudes have changed as a result of changes in the educational system. As a result, we would like to present a better comprehension of the sentiment dynamics of online education adoption.