Sentiment Analysis of Face-to-face Learning during Covid-19 Pandemic using Twitter Data

Ghanim Kanugrahan, Alfan Farizki Wicaksono

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Covid-19 pandemic has massive impacts on the activity of human in the world, including in Indonesia. To reduce the transmission of the virus, Indonesian government issues a policy to restrict daily public activities, affecting key national sectors, such as education systems. All learning activities are switched from the conventional face-to-face mode to being remote via the use of the Internet. After the pandemic begins to subside, the government then plans to reopen all schools and to allow face-to-face learning. However, this decision has sparked controversy in the social media, including Twitter. This paper describes a methodology to perform sentiment analysis on a collection of tweets that are in connection with the restart of the face-to-face learning mode. In particular, our experiments using hand-crafted features based on the tweets demonstrate that data-driven models are useful for automatic sentiment orientation classification on Twitter data. The best model achieved in this study has 69,1% accuracy, 68.6% precision, 69.1% recall, and 67,8% F1-Score. This result is achieved by using unigram, Support Vector Machine, and tweet + number of words (count) feature combinations.

Original languageEnglish
Title of host publicationProceedings - 2021 8th International Conference on Advanced Informatics
Subtitle of host publicationConcepts, Theory, and Application, ICAICTA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665417433
DOIs
Publication statusPublished - 2021
Event8th International Conference on Advanced Informatics: Concepts, Theory, and Application, ICAICTA 2021 - Virtual, Bandung, Indonesia
Duration: 29 Sep 202130 Sep 2021

Publication series

NameProceedings - 2021 8th International Conference on Advanced Informatics: Concepts, Theory, and Application, ICAICTA 2021

Conference

Conference8th International Conference on Advanced Informatics: Concepts, Theory, and Application, ICAICTA 2021
Country/TerritoryIndonesia
CityVirtual, Bandung
Period29/09/2130/09/21

Keywords

  • ANN
  • Covid-19
  • face-to-face learning
  • machine learning
  • SVM

Fingerprint

Dive into the research topics of 'Sentiment Analysis of Face-to-face Learning during Covid-19 Pandemic using Twitter Data'. Together they form a unique fingerprint.

Cite this