COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ

Derya Gündüz Hoşgör; Hacer Güngördü; Haydar Hoşgör

doi:10.33723/rs.1303402

EN TR

Analysis of Public Interest in Different Emotional State Expressions During and Before the COVID-19 Pandemic Using Google Trends

Abstract

The main objective of this study is to examine whether there is a statistically significant difference in the public's interest in different emotional expressions during and before the Covid-19 pandemic. Data for the study was obtained from Google Trends, a publicly available database. The pre-pandemic period was set from March 2019-2020, and the pandemic period was set from March 2020-2021. 25 search terms related to emotional expressions were scanned, and searches were focused in Turkey across all categories. Student's t-test was used for data analysis collected between February 20-23, 2023. The top three search terms with the highest average search volume during the pre-pandemic period were "death" (81.6), "anxiety" (79.0), and "depression" (74.4), respectively. During the pandemic period, the top three were "hallucination" (66.9), "anxiety" (64.9), and "anger" (54.9), respectively. It was found that the search frequencies of the terms "melancholy", "uncertainty", "paranoia", and "hallucination" on Google increased significantly (p<0.05) during the Covid-19 pandemic period. Surprisingly, it was also found that the average search frequencies of the terms "anxiety", "depression", "stress", "panic attack", "anxiousness", "suicide", "fear", "death", "loneliness", "obsession", "despair", and "boredom" also significantly increased (p<0.05) before the Covid-19 pandemic. These findings highlight the need for interventions to address the mental health consequences of the pandemic, and demonstrate the usefulness of Google Trends as a tool for monitoring public interest in emotional expressions.

Keywords

Covid-19, Pandemic, Google Trends, Emotional State, Turkey

Project Number

---

COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ

Abstract

Bu çalışmanın temel amacı Covid-19 pandemisi sırasında ve öncesinde halkın farklı duygu durum ifadelerine yönelik ilgisinde istatistiki olarak anlamlı bir farklılık olup olmadığının incelenmesidir. Çalışmanın verileri ücretsiz ve halka açık bir veri tabanı olan Google Trendler’den elde edilmiştir. Covid-19 öncesi dönemi için Mart 2019-2020 yıl aralığı, pandemi dönemi içinse Mart 2020-2021 dönemi referans alınmış ve 25 adet arama terimi taranmıştır. Tarama işlemi yapılırken Türkiye ve tüm kategoriler seçilerek aramalar yoğunlaştırılmıştır. 20-23 Şubat 2023 tarihleri arasında toplanan verilerin analizinde Student’s t-testi kullanılmıştır. Pandemi öncesi dönemde en fazla arama hacmi ortalamasına sahip olan ilk üç terimin sırayla “ölüm” (81,6), “anksiyete” (79,0), “depresyon” (74,4); pandemi dönemindekilerin ise sırayla “halüsinasyon” (66,9), “anksiyete” (64,9) ve “öfke” (54,9) olduğu saptanmıştır. “Melankoli”, “belirsizlik”, “paranoya” ve “halüsinasyon” terimlerinin Google’da aranma sıklıklarının Covid-19 pandemisi döneminde istatistiki olarak anlamlı derecede (p<0,05) arttığı belirlenmiştir. “Anksiyete”, “depresyon”, “stres”, “panik atak”, “kaygı”, “intihar”, “korku”, “ölüm”, “yalnızlık”, “takıntı”, “çaresizlik” ve “can sıkıntısı” terimlerinin ortalama aranma sıklıklarının ise şaşırtıcı olarak Covid-19 pandemisi öncesinde istatistiki olarak anlamlı derecede arttığı (p<0,05) tespit edilmiştir. Bu sonuçlar, pandeminin halkın duygusal iyi oluş hali üzerinde derin etkileri olduğunu ve ruhsal sağlığa etkilerine yönelik müdahalelere ihtiyaç duyulduğunu göstermektedir.

Keywords

Covid-19, Pandemi, Google Trendler, Duygu Durumu, Türkiye

Supporting Institution

---

Project Number

---

Thanks

---

References

Adams-Prassl, A., Boneva, T., Golin, M., & Rauh, C. (2022). The impact of the coronavirus lockdown on mental health: evidence from the United States. Economic Policy, 37(109), 139-155. https://doi.org/10.1093/epolic/eiac002
Avcı, K. (2021). Türkiye’de COVID-19 ile ilgili web arama davranışlarının incelenmesi: Google trendleri kullanan bir dijital epidemiyoloji çalışması. Türk Hijyen ve Deneysel Biyoloji Dergisi, 78(2), 133-146. https://dx.doi.org/10.5505/TurkHijyen.2021.48991
Brodeur, A., Clark, A. E., Fleche, S., & Powdthavee, N. (2021). COVID-19, lockdowns and well-being: Evidence from Google Trends. Journal of Public Economics, 193, 104346. https://doi.org/10.1016/j.jpubeco.2020.104346
Chintalapudi, N., Battineni, G., & Amenta, F. (2021). Sentimental analysis of COVID-19 tweets using deep learning models. Infectious Disease Reports, 13(2), 329-339. https://doi.org/10.3390/idr13020032
Dubey, S., Biswas, P., Ghosh, R., Chatterjee, S., Dubey, M. J., Chatterjee, S., ... & Lavie, C. J. (2020). Psychosocial impact of COVID-19. Diabetes & Metabolic Syndrome: Clinical Research & Reviews, 14(5), 779-788. https://doi.org/10.1016/j.dsx.2020.05.035
Gao, J., Zheng, P., Jia, Y., Chen, H., Mao, Y., Chen, S., ... & Dai, J. (2020). Mental health problems and social media exposure during COVID-19 outbreak. Plos One, 15(4), e0231924. https://doi.org/10.1371/journal.pone.0231924
Gianfredi, V., Provenzano, S., & Santangelo, O. E. (2021). What can internet users' behaviours reveal about the mental health impacts of the COVID-19 pandemic? A systematic review. Public Health, 198, 44-52. https://doi.org/10.1016/j.puhe.2021.06.024
Hagen, D., Lai, A. Y., & Goldmann, E. (2022). Trends in negative emotions throughout the COVID-19 pandemic in the United States. Public Health, 212, 4-6. https://doi.org/10.1016/j.puhe.2022.08.009
Hoerger, M., Alonzi, S., Perry, L. M., Voss, H. M., Easwar, S., & Gerhart, J. I. (2020). Impact of the COVID-19 pandemic on mental health: Real-time surveillance using Google Trends. Psychological Trauma: Theory, Research, Practice, and Policy, 12(6), 567-568. https://psycnet.apa.org/doi/10.1037/tra0000872
Kristoufek, L., Moat, H. S., & Preis, T. (2016). Estimating suicide occurrence statistics using Google Trends. EPJ data science, 5, 1-12. http://dx.doi.org/10.1140/epjds/s13688-016-0094-0

Li, X., Zhou, M., Wu, J., Yuan, A., Wu, F., & Li, J. (2020). Analyzing COVID-19 on online social media: Trends, sentiments and emotions. ArXiv Preprint ArXiv:2005.14464. https://doi.org/10.48550/arXiv.2005.14464
Lwin, M. O., Lu, J., Sheldenkar, A., Schulz, P. J., Shin, W., Gupta, R., & Yang, Y. (2020). Global sentiments surrounding the COVID-19 pandemic on Twitter: analysis of Twitter trends. JMIR Public Health and Surveillance, 6(2), e19447. https://doi.org/10.2196/19447
Niederkrotenthaler, T., Fu, K. W., Yip, P. S., Fong, D. Y., Stack, S., Cheng, Q., & Pirkis, J. (2012). Changes in suicide rates following media reports on celebrity suicide: A meta-analysis. Journal of Epidemiol Community Health, 66(11), 1037-1042. http://dx.doi.org/10.1136/jech-2011-200707
Pfefferbaum, B., & North, C. S. (2020). Mental health and the Covid-19 pandemic. New England Journal of Medicine, 383(6), 510-512. https://doi.org/10.1056/NEJMp2008017
Rogers, J. P., Chesney, E., Oliver, D., Pollak, T. A., McGuire, P., Fusar-Poli, P., ... & David, A. S. (2020). Psychiatric and neuropsychiatric presentations associated with severe coronavirus infections: A systematic review and meta-analysis with comparison to the COVID-19 pandemic. The Lancet Psychiatry, 7(7), 611-627. https://doi.org/10.1016/S2215-0366(20)30203-0
Southwick, L., Guntuku, S. C., Klinger, E. V., Seltzer, E., McCalpin, H. J., & Merchant, R. M. (2021). Characterizing COVID-19 content posted to TikTok: public sentiment and response during the first phase of the COVID-19 pandemic. Journal of Adolescent Health, 69(2), 234-241. https://doi.org/10.1016/j.jadohealth.2021.05.010
Taquet, M., Geddes, J. R., Husain, M., Luciano, S., & Harrison, P. J. (2021). 6-month neurological and psychiatric outcomes in 236 379 survivors of COVID-19: A retrospective cohort study using electronic health records. The Lancet Psychiatry, 8(5), 416-427. https://doi.org/10.1371/journal.pmed.1003773
Ü. Dörttepe, Z., Hoşgör, H., & Sağcan, H. (2021). The effect of COVID-19 phobia on perceived stress: The sample of prehospital emergency care professionals. Journal of Academic Value Studies, 7(1), 31-40. https://doi.org/10.29228/javs.49250
Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., & Ho, R. C. (2020). Immediate psychological responses and associated factors during the initial stage of the 2019 coronavirus disease (COVID-19) epidemic among the general population in China. International Journal of Environmental Research and Public Health, 17(5), 1729. https://doi.org/10.3390/ijerph17051729
Wang, J., Fan, Y., Palacios, J., Chai, Y., Guetta-Jeanrenaud, N., Obradovich, N., ... & Zheng, S. (2022). Global evidence of expressed sentiment alterations during the COVID-19 pandemic. Nature Human Behaviour, 6(3), 349-358. https://doi.org/10.1038/s41562-022-01312-y
Xiong, J., Lipsitz, O., Nasri, F., Lui, L. M., Gill, H., Phan, L., ... & McIntyre, R. S. (2020). Impact of COVID-19 pandemic on mental health in the general population: A systematic review. Journal of Affective Disorders, 277, 55-64. https://doi.org/10.1016/j.jad.2020.08.001

Details

Primary Language

Turkish

Subjects

Behaviour-Personality Assessment in Psychology

Journal Section

Research Article

Authors

Derya Gündüz Hoşgör ^*
0000-0002-1377-4617
Türkiye

Hacer Güngördü
0000-0003-3978-9259
Türkiye

Haydar Hoşgör
0000-0002-1174-1184
Türkiye

Early Pub Date

July 30, 2023

Publication Date

July 31, 2023

Submission Date

May 27, 2023

Acceptance Date

July 5, 2023

Published in Issue

Year 2023 Volume: 6 Number: 3

DOI

https://doi.org/10.33723/rs.1303402

IZ

https://izlik.org/JA84NE99TH

APA

Gündüz Hoşgör, D., Güngördü, H., & Hoşgör, H. (2023). COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ. R&S - Research Studies Anatolia Journal, 6(3), 267-282. https://doi.org/10.33723/rs.1303402

AMA

1.Gündüz Hoşgör D, Güngördü H, Hoşgör H. COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ. R&S - Research Studies Anatolia Journal. 2023;6(3):267-282. doi:10.33723/rs.1303402

Chicago

Gündüz Hoşgör, Derya, Hacer Güngördü, and Haydar Hoşgör. 2023. “COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ”. R&S - Research Studies Anatolia Journal 6 (3): 267-82. https://doi.org/10.33723/rs.1303402.

EndNote

Gündüz Hoşgör D, Güngördü H, Hoşgör H (July 1, 2023) COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ. R&S - Research Studies Anatolia Journal 6 3 267–282.

IEEE

[1]D. Gündüz Hoşgör, H. Güngördü, and H. Hoşgör, “COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ”, R&S - Research Studies Anatolia Journal, vol. 6, no. 3, pp. 267–282, July 2023, doi: 10.33723/rs.1303402.

ISNAD

Gündüz Hoşgör, Derya - Güngördü, Hacer - Hoşgör, Haydar. “COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ”. R&S - Research Studies Anatolia Journal 6/3 (July 1, 2023): 267-282. https://doi.org/10.33723/rs.1303402.

JAMA

1.Gündüz Hoşgör D, Güngördü H, Hoşgör H. COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ. R&S - Research Studies Anatolia Journal. 2023;6:267–282.

MLA

Gündüz Hoşgör, Derya, et al. “COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ”. R&S - Research Studies Anatolia Journal, vol. 6, no. 3, July 2023, pp. 267-82, doi:10.33723/rs.1303402.

Vancouver

1.Derya Gündüz Hoşgör, Hacer Güngördü, Haydar Hoşgör. COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ. R&S - Research Studies Anatolia Journal. 2023 Jul. 1;6(3):267-82. doi:10.33723/rs.1303402

Analysis of Public Interest in Different Emotional State Expressions During and Before the COVID-19 Pandemic Using Google Trends

Abstract

Keywords

Project Number

COVID-19 PANDEMİSİ VE ÖNCESİNDE HALKIN FARKLI DUYGU DURUM İFADELERİNE İLGİSİNİN GOOGLE TRENDLER ÜZERİNDEN ANALİZİ

Abstract

Keywords

Supporting Institution

Project Number

Thanks

References

Details

Primary Language

Subjects

Journal Section

Authors

Early Pub Date

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

Cite