Skip to main content
SpringerLink
Log in

Identifying Covid-19 Impact on Peruvian Mental Health During Lockdown Using Social Network

  • Conference paper
  • First Online:
Book cover Information Management and Big Data (SIMBig 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1410))

Included in the following conference series:

  • 724 Accesses

Abstract

The actual outbreak generated by SARS-CoV-2, presented a challenge to the governments because PublicS Health, Economy, and Society are different in every country so actions must fit considering these previous conditions. South America is a region with developing countries, limitations, problems and the pandemic highlighted them. Peru is a country with good initial policies to contain the pandemic, a lockdown started on March 15 and lasted more than 100 days. By consequence, people were forced to change daily activities and of course, social and mental problems started to grow. The actual study wants to identify the covid-19 impact on the Social Network, Twitter filtering posts related to the topic. The initial findings present a high interest in the topic during the first week and a decreasing pattern in the last weeks.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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. WHO: WHO Coronavirus Disease (COVID-19) Dashboard. https://covid19.who.int. Accessed 14 June 2020

  2. Brouwer, E.D., Raimondi, D., Moreau, Y.: Modeling the COVID-19 outbreaks and the effectiveness of the containment measures adopted across countries. medRxiv, p. 2020.04.02.20046375, April 2020. https://doi.org/10.1101/2020.04.02.20046375, https://www.medrxiv.org/content/10.1101/2020.04.02.20046375v3

  3. Chong Ng Kee Kwong, K., Mehta, P.R., Shukla, G., Mehta, A.R.: COVID-19, SARS and MERS: a neurological perspective. J. Clin. Neurosci. May 2020. https://doi.org/10.1016/j.jocn.2020.04.124, http://www.sciencedirect.com/science/article/pii/S0967586820311851

  4. Feng, L.S., et al.: Psychological distress in the shadow of the COVID-19 pandemic: preliminary development of an assessment scale. Psychiatry Res. 291, 113202, September 2020. https://doi.org/10.1016/j.psychres.2020.113202, http://www.sciencedirect.com/science/article/pii/S016517812031595X

  5. Drias, H.H., Drias, Y.: Mining twitter data on covid-19 for sentiment analysis and frequent patterns discovery. medRxiv (2020). https://doi.org/10.1101/2020.05.08.20090464, https://www.medrxiv.org/content/early/2020/05/18/2020.05.08.20090464

  6. Jordan, S.E., Hovet, S.E., Fung, I.C.H., Liang, H., Fu, K.W., Tse, Z.T.H.: Using Twitter for public health surveillance from monitoring and prediction to public response. Data 4(1), 6 (2019). https://doi.org/10.3390/data4010006, https://www.mdpi.com/2306-5729/4/1/6

  7. Abd-Alrazaq, A., Alhuwail, D., Househ, M., Hamdi, M., Shah, Z.: Top concerns of tweeters during the covid-19 pandemic: infoveillance study. J. Med. Internet Res. 22(4), e19061 (2020). https://doi.org/10.2196/19016

    Article  Google Scholar 

  8. Caycho-Rodriguez, T., Carbajal-Leon, C., Vilca, L.W., Heredia-Mongrut, J., Gallegos, M.: COVID-19 y salud mental en policías peruanos: resultados preliminares. ACTA MEDICA PERUANA 37(3), October 2020. https://doi.org/10.35663/amp.2020.373.1503, https://amp.cmp.org.pe/index.php/AMP/article/view/1503

  9. Diseases, T.L.I.: The intersection of COVID-19 and mental health. Lancet Infect. Dis. 0(0), October 2020. https://doi.org/10.1016/S1473-3099(20)30797-0, https://www.thelancet.com/journals/laninf/article/PIIS1473-3099(20)30797-0/abstract

  10. Sinnenberg, L., Buttenheim, A.M., Padrez, K., Mancheno, C., Ungar, L., Merchant, R.M.: Twitter as a tool for health research: a systematic review. Am. J. Public Health 107(1), e1–e8 (2017)

    Article  Google Scholar 

  11. Breland, J.Y., Quintiliani, L.M., Schneider, K.L., May, C.N., Pagoto, S.: Social media as a tool to increase the impact of public health research. Am. J. Public Health 107(12), 1890 (2017)

    Article  Google Scholar 

  12. Yepes, A.J., MacKinlay, A., Han, B.: Investigating public health surveillance using twitter. Proc. BioNLP 15, 164–170 (2015)

    Article  Google Scholar 

  13. Chew, C., Eysenbach, G.: Pandemics in the age of twitter: content analysis of tweets during the 2009 H1N1 outbreak. PLoS ONE 5(11), p14118 (2010)

    Article  Google Scholar 

  14. Saire, J.E.C.: Building intelligent indicators to detect dengue epidemics in brazil using social networks. In: 2019 IEEE Colombian Conference on Applications in Computational Intelligence (ColCACI), pp. 1–5. IEEE (2019)

    Google Scholar 

  15. Saire, J.E.C., Navarro, R.C.: What is the people posting about symptoms related to coronavirus in bogota, colombia? arXiv preprint arXiv:2003.11159 (2020)

  16. Chire Saire, J.E.: Infoveillance based on social sensors to analyze the impact of covid19 in South American population (2020). https://doi.org/10.1101/2020.04.06.20055749

  17. Chire Saire, J.E., Pineda-Briseno, A.: Text mining approach to analyze coronavirus impact: Mexico city as case of study. medRxiv (2020). https://doi.org/10.1101/2020.05.07.20094466, https://www.medrxiv.org/content/early/2020/05/12/2020.05.07.20094466

  18. Ear, S.: Towards effective emerging infectious diseases surveillance: evidence from Kenya, Peru, Thailand, and the U.S.-Mexico (2012). https://siepr.stanford.edu/research/publications/ towards-effective-emerging-infectious-diseases-surveillanceevidence- kenya-peru

  19. Huarcaya-Victoria, J.: Consideraciones sobre la salud mental en la pandemia de COVID-19. Revista Peruana de Medicina Experimental y Salud Pública 37(2), 327–34, April 2020. https://doi.org/10.17843/rpmesp.2020.372.5419, https://rpmesp.ins.gob.pe/index.php/rpmesp/article/view/5419

  20. Lee, S.A.: Coronavirus anxiety scale: a brief mental health screener for COVID-19 related anxiety. Death Stud. 44(7), 393–401 (2020). https://doi.org/10.1080/07481187.2020.1748481

    Article  Google Scholar 

  21. Singh, P., Dwivedi, Y.K., Kahlon, K.S., Sawhney, R.S., Alalwan, A.A., Rana, N.P.: Smart monitoring and controlling of government policies using social media and cloud computing. Inf. Syst. Front. 22(2), 315–337 (2020). https://doi.org/10.1007/s10796-019-09916-y

    Article  Google Scholar 

  22. 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 Surv. 6(2), e18828 (2020). https://doi.org/10.2196/18828, https://publichealth.jmir.org/2020/2/e18828/, company: JMIR Public Health and Surveillance Distributor: JMIR Public Health and Surveillance Institution: JMIR Public Health and Surveillance Label: JMIR Public Health and Surveillance Publisher: JMIR Publications Inc., Toronto, Canada

  23. Rajkumar, R.P.: COVID-19 and mental health: a review of the existing literature. Asian J. Psychiatry 52, 102066, August 2020. https://doi.org/10.1016/j.ajp.2020.102066, http://www.sciencedirect.com/science/article/pii/S1876201820301775

  24. Liang, Y., Zheng, X., Zeng, D.D.: A survey on big data-driven digital phenotyping of mental health. Inf. Fusion 52, 290–307, December 2019. https://doi.org/10.1016/j.inffus.2019.04.001, http://www.sciencedirect.com/science/article/pii/S1566253518305244

  25. Mejia, C.R., et al.: The media and their informative role in the face of the coronavirus disease 2019 (COVID-19): validation of fear perception and magnitude of the issue (MED-COVID-19). Electron. J. General Med. 17(6), em239, April 2020. https://doi.org/10.29333/ejgm/7946, https://www.ejgm.co.uk/article/the-media-and-their-informative-role-in-the-face-of-the-coronavirus-disease-2019-covid-19-validation-7946

  26. de Melo, T., Figueiredo, C.M.S.: A first public dataset from Brazilian twitter and news on COVID-19 in Portuguese. Data Brief 32, 106179, October 2020. https://doi.org/10.1016/j.dib.2020.106179, http://www.sciencedirect.com/science/article/pii/S2352340920310738

  27. Zhang, T.: Data mining can play a critical role in COVID-19 linked mental health studies. Asian J. Psychiatry 54, 102399, December 2020. https://doi.org/10.1016/j.ajp.2020.102399, http://www.sciencedirect.com/science/article/pii/S1876201820305128

  28. Arslan, G., Yıldırım, M., Tanhan, A., Buluş, M., Allen, K.A.: Coronavirus stress, optimism-pessimism, psychological inflexibility, and psychological health: psychometric properties of the coronavirus stress measure. Int. J. Mental Health Addict. (2020). https://doi.org/10.1007/s11469-020-00337-6

    Article  Google Scholar 

  29. Benítez, M.A., Velasco, C., Sequeira, A.R., Henríquez, J., Menezes, F.M., Paolucci, F.: Responses to COVID-19 in five Latin American countries. Health Policy Technol. August 2020. https://doi.org/10.1016/j.hlpt.2020.08.014, http://www.sciencedirect.com/science/article/pii/S2211883720300861

  30. Singh, P., Singh, S., Sohal, M., Dwivedi, Y.K., Kahlon, K.S., Sawhney, R.S.: Psychological fear and anxiety caused by COVID-19: insights from Twitter analytics. Asian J. Psychiatry 54, 102280, December 2020. https://doi.org/10.1016/j.ajp.2020.102280, https://covid19.elsevierpure.com/en/publications/psychological-fear-and-anxiety-caused-by-covid-19-insights-from-t

Download references

Author information

Authors and Affiliations

  1. Institute of Mathematics and Computer Science (ICMC), University of São Paulo (USP), São Carlos, SP, Brazil

    Josimar E. Chire Saire

  2. Facultad de Ingeniería, Universidad Privada del Norte, Trujillo, Peru

    Jimy Frank Oblitas Cruz

Authors
  1. Josimar E. Chire Saire
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jimy Frank Oblitas Cruz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Josimar E. Chire Saire .

Editor information

Editors and Affiliations

  1. Stanford University, Stanford, CA, USA

    Juan Antonio Lossio-Ventura

  2. Visibilia, São Paulo, Brazil

    Jorge Carlos Valverde-Rebaza

  3. University of Valencia, Valencia, Spain

    Eduardo Díaz

  4. Universidad del Pacífico, Lima, Peru

    Hugo Alatrista-Salas

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Saire, J.E.C., Cruz, J.F.O. (2021). Identifying Covid-19 Impact on Peruvian Mental Health During Lockdown Using Social Network. In: Lossio-Ventura, J.A., Valverde-Rebaza, J.C., Díaz, E., Alatrista-Salas, H. (eds) Information Management and Big Data. SIMBig 2020. Communications in Computer and Information Science, vol 1410. Springer, Cham. https://doi.org/10.1007/978-3-030-76228-5_34

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-76228-5_34

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-76227-8

  • Online ISBN: 978-3-030-76228-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation