Skip to main content

Social Versus Physical Distancing: Analysis of Public Health Messages at the Start of COVID-19 Outbreak in Malaysia Using Natural Language Processing

  • Conference paper
  • First Online:
Book cover Proceedings of the 8th International Conference on Computational Science and Technology

Abstract

The study presents an attempt to analyse how social media netizens in Malaysia responded to the calls for “Social Distancing” and “Physical Distancing” as the newly recommended social norm was introduced to the world as a response to the COVID-19 global pandemic. The pandemic drove a sharp increase in social media platforms’ use as a public health communication platform since the first wave of the COVID-19 outbreak in Malaysia in April 2020. We analysed thousands of tweets posted by Malaysians daily between January 2020 and August 2021 to determine public perceptions and interactions patterns. The analysis focused on positive and negative reactions and the interchanges of uses of the recommended terminologies “social distancing” and “physical distancing”. Using linguistic analysis and natural language processing, findings dominantly indicate influences from the multilingual and multicultural values held by Malaysian netizens, as they embrace the concept of distancing as a measure of global public health safety.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 229.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 299.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 299.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Aisopos F, Papadakis G, Varvarigou T (2011) Sentiment analysis of social media content using N-gram graphs. In MM’11—Proceedings of the 2011 ACM multimedia conference and co-located workshops—WSM’11: 3rd ACM social media workshop

    Google Scholar 

  2. Al-Rfou R, Perozzi B, Skiena S (2013) Polyglot: distributed word representations for multilingual NLP. In: CoNLL 2013—17th conference on computational natural language learning, proceedings

    Google Scholar 

  3. Babulal V, Othman NZ (2020) Sri Petaling Tabligh gathering remains Msia’s largest COVID-19 cluster. New Straits Times, (September). Retrieved from: https://bit.ly/tabligh_gathering

  4. Batrinca B, Treleaven PC (2014) Social media analytics: a survey of techniques, tools and platforms. AI Soc. https://doi.org/10.1007/s00146-014-0549-4

    Article  Google Scholar 

  5. Bird S (2006) NLTK. COLING-ACL ‘06: proceedings of the COLING/ACL on Interactive presentation sessions July 2006, pp 69–72

    Google Scholar 

  6. Cavalieri DC, Palazuelos-Cagigas SE, Bastos-Filho TF, Sarcinelli-Filho M (2016) Combination of language models for word prediction: an exponential approach. IEEE/ACM Trans Audio Speech Lang Process

    Google Scholar 

  7. Chang YC, Ku CH, Chen CH (2019) Social media analytics: extracting and visualising Hilton hotel ratings and reviews from TripAdvisor. Int J Inf Manage. https://doi.org/10.1016/j.ijinfomgt.2017.11.001

    Article  Google Scholar 

  8. Chen Y, Skiena S (2014) Building sentiment lexicons for all major languages. In: 52nd annual meeting of the association for computational linguistics, ACL 2014—proceedings of the conference. https://doi.org/10.3115/v1/p14-2063

  9. Devlin J, Chang MW, Lee K, Toutanova K (2019) BERT: pre-training of deep bidirectional transformers for language understanding. In: NAACL HLT 2019—2019 Conference of the North American chapter of the association for computational linguistics: human language technologies—proceedings of the conference

    Google Scholar 

  10. Dredze M, Broniatowski DA, Hilyard KM (2016) Zika vaccine misconceptions: a social media analysis. Vaccine 34(30):3441

    Article  Google Scholar 

  11. Fan W, Gordon MD (2014) The power of social media analytics. Commun ACM. https://doi.org/10.1145/2602574

    Article  Google Scholar 

  12. Friedman N, Geiger D, Goldszmidt M (1997) Bayesian network classifiers. Mach Learn. https://doi.org/10.1002/9780470400531.eorms0099

    Article  MATH  Google Scholar 

  13. Han J, Kamber M, Pei J (2012) Data mining: concepts and techniques. Morgan Kaufmann. https://doi.org/10.1016/C2009-0-61819-5

  14. Hart M (2020) WHO changes “social distancing” to “physical distancing”. Nerdist. Retrieved from: https://nerdist.com/article/social-distancing-changed-physical-distancing/

  15. Hofmann T (2001) Unsupervised learning by probabilistic latent semantic analysis. Mach Learn. https://doi.org/10.1023/A:1007617005950

    Article  MATH  Google Scholar 

  16. Husein Z (2018) Malaya, natural-language-toolkit library for Bahasa Malaysia, powered by deep learning tensorflow. Github. https://github.com/huseinzol05/malaya

  17. Juan SS, Ismail MFC, Ujir H, Hipiny I (2020) Language modelling for a low-resource language in Sarawak, Malaysia. LNEE 619:147–158. https://doi.org/10.1007/978-981-15-1289-6_14

    Article  Google Scholar 

  18. Kaos J Jr (2020) Health DG : 171 COVID-19 cases linked to church gathering, wedding ceremony. The Star. Retrieved from https://bit.ly/thestar_covid19

  19. Karafi M, Cernock JH (2010) Recurrent Neural network language modeling, pp 1045–1048. https://doi.org/10.1021/jp056727x

  20. Kaur PC, Ghorpade T, Mane V (2016) Topic extraction and sentiment classification by using latent dirichlet Markov allocation and sentiwordnet. In: ACM international conference proceeding series. https://doi.org/10.1145/2979779.2979865

  21. Kayes ASM, Islam MS, Watters PA, Ng A, Kayesh H (2020) Automated measurement of attitudes towards social distancing using social media: a COVID-19 case study. Preprints, April. https://doi.org/10.20944/preprints202004.0057.v1

  22. Kibriya AM, Frank E, Pfahringer B, Holmes G (2004) Multinomial naive bayes for text categorisation revisited. Lect Notes Artif Intell (Subseries of Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-540-30549-1_43

    Article  Google Scholar 

  23. Lee I (2018) Social media analytics for enterprises: typology, methods, and processes. Bus Horiz. https://doi.org/10.1016/j.bushor.2017.11.002

    Article  Google Scholar 

  24. Mat NFC, Edinur HA, Razab MKAA, Safuan S (2020) A single mass gathering resulted in massive transmission of COVID-19 infections in Malaysia with further international spread. J Travel Med 27(3):1–4

    Google Scholar 

  25. Nazar R, Renau I (2012) Google Books N-gram Corpus used as a Grammar Checker. In: Proceedings of the EACL 2012 workshop on computational linguistics and writing

    Google Scholar 

  26. Öztürk N, Ayvaz S (2018) Sentiment analysis on Twitter: a text mining approach to the Syrian refugee crisis. Telemat Inform

    Google Scholar 

  27. Thakor P, Sasi S (2015) Ontology-based sentiment analysis process for social media content. In: INNS conference on big data, pp 199–207

    Google Scholar 

  28. Yang Z, Dai Z, Yang Y, Carbonell J, Salakhutdinov R, Le QV (2019) XLNet: generalised autoregressive pretraining for language understanding. Adv Neural Inf Process Syst

    Google Scholar 

  29. Zeng D, Chen H, Lusch R, Li SH (2010) Social media analytics and intelligence. IEEE Intell Syst 25(6). https://doi.org/10.1109/MIS.2010.151

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sarah Samson Juan .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Juan, S.S., Saee, S., Mohamad, F. (2022). Social Versus Physical Distancing: Analysis of Public Health Messages at the Start of COVID-19 Outbreak in Malaysia Using Natural Language Processing. In: Alfred, R., Lim, Y. (eds) Proceedings of the 8th International Conference on Computational Science and Technology. Lecture Notes in Electrical Engineering, vol 835. Springer, Singapore. https://doi.org/10.1007/978-981-16-8515-6_44

Download citation

Publish with us

Policies and ethics