Analysis The Opinion of School-from-Home during The COVID-19 Pandemic using LSTM Approach

Abstract

The purpose of opinion analysis in this research is to perceive public responses concerning School-From-Home (SFH) policy during the pandemic in attempt to curb virus spread and worry about new cluster emergences. The policy entails diverse reactions from the societies, including the citizens in virtual world through their chirps in social media, such as Twitter. Analysis on the social media has proved that it has remarkable potentials to apprehend public opinions on various issues. The opinion analysis was performed to get insights about public perception towards SFH policy. As initially predicted, the result of our analysis would show that the public perceptions towards SFH would be mainly negative. The researcher adopted LSTM model as a deep learning approach. Moreover, implementing the N-Gram extraction technique was able to improve the model’s performance. Model performance accuracy reached 83.30%. It is concluded that the increasing of model accuracy is about 0.018%. While the running time efficiency of LSTM has improved 19.4%. The results of the analysis of SFH’s opinion were 77.90% negative and 22.10% positive.