Abstract
Studies on digital interaction in emergent users’ population are rare. We analyse the electronic data generated by users from Pakistan on Google Search Engine and WhatsApp to understand their information-seeking behaviour during the first wave of the Covid-19 pandemic. We study how the Pakistani public developed their understanding about the disease, (its origin, cures, and preventive measures to name a few) through digital media. Understanding this information seeking behaviour will allow corrective actions to be taken by health policymakers to better inform the public in future health crises through electronic media, as well as the digital media platforms and search engines to address misinformation among the users in the emergent markets.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
References
Coronavirus attitude tracker survey report - wave 8 (2020). https://gallup.com.pk/wp/wp-content/uploads/2020/10/Gallup-Pakistan-Coronavirus-Attitude-Tracker-Survey-Wave-8-.pdf
NCC rules out comlete lockdown (2020). https://www.dawn.com/news/1588511. Accessed 11 Nov 2021
Second wave (2020). https://www.dawn.com/news/1583507/second-wave. Accessed 11 Nov 2021
Ayyoubzadeh, S.M., Ayyoubzadeh, S.M., Zahedi, H., Ahmadi, M., Kalhori, S.R.N.: Predicting COVID-19 incidence through analysis of google trends data in Iran: data mining and deep learning pilot study. JMIR Public Health Surveill. 6(2), e18828 (2020)
Badell-Grau, R.A., Cuff, J.P., Kelly, B.P., Waller-Evans, H., Lloyd-Evans, E.: Investigating the prevalence of reactive online searching in the COVID-19 pandemic: infoveillance study. J. Med. Internet Res. 22(10), e19791 (2020)
Bento, A.I., Nguyen, T., Wing, C., Lozano-Rojas, F., Ahn, Y.Y., Simon, K.: Evidence from internet search data shows information-seeking responses to news of local COVID-19 cases. Proc. Natl. Acad. Sci. 117(21), 11220–11222 (2020)
Bilal, A., Rextin, A., Kakakhel, A., Nasim, M.: Analyzing emergent users’ text messages data and exploring its benefits. IEEE Access 7, 2870–2879 (2018)
Blandizzi, C., Scarpignato, C.: Gastrointestinal drugs. In: Side Effects of Drugs Annual, vol. 33, pp. 741–767. Elsevier (2011)
Braun, V., Clarke, V.: Using thematic analysis in psychology. Qual. Res. Psychol. 3(2), 77–101 (2006)
Chen, L., Wang, X., Peng, T.Q.: Nature and diffusion of gynecologic cancer-related misinformation on social media: analysis of tweets. J. Med. Internet Res. 20(10), e11515 (2018)
Chou, W.Y.S., Oh, A., Klein, W.M.: Addressing health-related misinformation on social media. JAMA 320(23), 2417–2418 (2018)
Datta, S.S., et al.: Progress and challenges in measles and rubella elimination in the who European region. Vaccine 36(36), 5408–5415 (2018)
Davis, M.: Habituation and sensitization of a startle-like response elicited by electrical stimulation at different points in the acoustic startle circuit. In: Sensory Functions, pp. 67–78. Elsevier (1981)
Denworth, L.: Overcoming psychological biases is the best treatment against COVID-19 yet (2020). https://www.scientificamerican.com/article/overcoming-psychological-biases-is-the-best-treatment-against-covid-19-yet/. Accessed 11 Nov 2021
Depoux, A., Martin, S., Karafillakis, E., Preet, R., Wilder-Smith, A., Larson, H.: The pandemic of social media panic travels faster than the COVID-19 outbreak (2020)
Dewsbury, D.A.: Effects of novelty of copulatory behavior: the coolidge effect and related phenomena. Psychol. Bull. 89(3), 464 (1981)
Filia, A., Bella, A., Del Manso, M., Baggieri, M., Magurano, F., Rota, M.C.: Ongoing outbreak with well over 4,000 measles cases in Italy from January to end August 2017 - what is making elimination so difficult? Eurosurveillance 22(37), 30614 (2017)
Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S., Brilliant, L.: Detecting influenza epidemics using search engine query data. Nature 457(7232), 1012–1014 (2009)
Gluck, M.A., Mercado, E., Myers, C.E.: Learning and Memory: From Brain to Behavior. Worth Publishers, New York (2008)
Gupta, L., Gasparyan, A.Y., Misra, D.P., Agarwal, V., Zimba, O., Yessirkepov, M.: Information and misinformation on COVID-19: a cross-sectional survey study. J. Korean Med. Sci. 35(27) (2020)
Hernández-García, I., Giménez-Júlvez, T.: Assessment of health information about COVID-19 prevention on the internet: infodemiological study. JMIR Public Health Surveill. 6(2), e18717 (2020)
Hu, D., et al.: More effective strategies are required to strengthen public awareness of COVID-19: evidence from google trends. J. Global Health 10(1) (2020)
Husnayain, A., Fuad, A., Su, E.C.Y.: Applications of google search trends for risk communication in infectious disease management: a case study of COVID-19 outbreak in Taiwan. Int. J. Infect. Dis. 95, 221–223 (2020)
Joshi, A.: Technology adoption by ‘emergent’ users: the user-usage model. In: Proceedings of the 11th Asia Pacific Conference on Computer Human Interaction, pp. 28–38 (2013)
Kim, K.D., Hossain, L.: Towards early detection of influenza epidemics by using social media analytics. In: DSS, pp. 36–41 (2014)
Kurian, S.J., et al.: Correlations between COVID-19 cases and google trends data in the united states: a state-by-state analysis. In: Mayo Clinic Proceedings, pp. 2370–2381. Elsevier (2020)
Kušen, E., Strembeck, M.: Politics, sentiments, and misinformation: an analysis of the twitter discussion on the 2016 Austrian presidential elections. Online Soc. Netw. Media 5, 37–50 (2018)
Liu, M., Caputi, T.L., Dredze, M., Kesselheim, A.S., Ayers, J.W.: Internet searches for unproven COVID-19 therapies in the United States. JAMA Internal Med. 180(8), 1116–1118 (2020)
Malani, A.N., Sherbeck, J.P., Malani, P.N.: Convalescent plasma and COVID-19. JAMA 324(5), 524 (2020)
Malcuit, G., Bastien, C., Pomerleau, A.: Habituation of the orienting response to stimuli of different functional values in 4-month-old infants. J. Exp. Child Psychol. 62(2), 272–291 (1996)
Moyer, M.W.: People drawn to conspiracy theories share a cluster of psychological features (2019). https://www.scientificamerican.com/article/people-drawn-to-conspiracy-theories-share-a-cluster-of-psychological-features/. Accessed 11 Nov 2021
Pennycook, G., McPhetres, J., Zhang, Y., Lu, J.G., Rand, D.G.: Fighting COVID-19 misinformation on social media: experimental evidence for a scalable accuracy-nudge intervention. Psychol. Sci. 31(7), 770–780 (2020)
Polgreen, P.M., Chen, Y., Pennock, D.M., Nelson, F.D., Weinstein, R.A.: Using internet searches for influenza surveillance. Clin. Infect. Dis. 47(11), 1443–1448 (2008)
Post, S., Bienzeisler, N., Lohöfener, M.: A desire for authoritative science? How citizens’ informational needs and epistemic beliefs shaped their views of science, news, and policymaking in the COVID-19 pandemic. Public Underst. Sci. 30(5), 496–514 (2021). https://doi.org/10.1177/09636625211005334
Rathore, F.A., Farooq, F.: Information overload and infodemic in the COVID-19 pandemic. JPMA J. Pak. Med. Assoc. 70(5), S162–S165 (2020)
Rovetta, A., Bhagavathula, A.S.: COVID-19-related web search behaviors and infodemic attitudes in Italy: infodemiological study. JMIR Public Health Surveill. 6(2), e19374 (2020)
Shah, M.: The failure of public health messaging about COVID-19 (2020. https://www.scientificamerican.com/article/the-failure-of-public-health-messaging-about-covid-19/. Accessed 11 Nov 2021
Sharma, K., Seo, S., Meng, C., Rambhatla, S., Dua, A., Liu, Y.: Coronavirus on social media: analyzing misinformation in twitter conversations. arXiv preprint arXiv:2003.12309 (2020)
Teng, Y., et al.: Dynamic forecasting of zika epidemics using google trends. PLoS ONE 12(1), e0165085 (2017)
Thapen, N., Simmie, D., Hankin, C., Gillard, J.: Defender: detecting and forecasting epidemics using novel data-analytics for enhanced response. PLoS ONE 11(5), e0155417 (2016)
Thompson, R.F., Spencer, W.A.: Habituation: a model phenomenon for the study of neuronal substrates of behavior. Psychol. Rev. 73(1), 16 (1966)
Walker, A., Hopkins, C., Surda, P.: The use of google trends to investigate the loss of smell related searches during COVID-19 outbreak. In: International Forum of Allergy & Rhinology. Wiley Online Library (2020)
Wang, C., et al.: Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in china. Int. J. Environ. Res. Public Health 17(5), 1729 (2020)
Waszak, P.M., Kasprzycka-Waszak, W., Kubanek, A.: The spread of medical fake news in social media-the pilot quantitative study. Health Policy Technol. 7(2), 115–118 (2018)
Wolf, M.S., et al.: Awareness, attitudes, and actions related to COVID-19 among adults with chronic conditions at the onset of the us outbreak: a cross-sectional survey. Ann. Internal Med. 173(2), 100–109 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Fatima, M., Rextin, A., Nasim, M., Yusuf, O. (2022). Digital Information Seeking and Sharing Behaviour During the COVID-19 Pandemic in Pakistan. In: Spezzano, F., Amaral, A., Ceolin, D., Fazio, L., Serra, E. (eds) Disinformation in Open Online Media. MISDOOM 2022. Lecture Notes in Computer Science, vol 13545 . Springer, Cham. https://doi.org/10.1007/978-3-031-18253-2_4
Download citation
DOI: https://doi.org/10.1007/978-3-031-18253-2_4
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-18252-5
Online ISBN: 978-3-031-18253-2
eBook Packages: Computer ScienceComputer Science (R0)