IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v20y2022i1p780-d1021703.html
   My bibliography  Save this article

What We Ask about When We Ask about Quarantine? Content and Sentiment Analysis on Online Help-Seeking Posts during COVID-19 on a Q&A Platform in China

Author

Listed:
  • Luanying Li

    (Faculty of Social Sciences, University of Macau, Avenida da Universidade, Taipa, Macau SAR 999078, China)

  • Lin Hua

    (Faculty of Health Sciences, University of Macau, Avenida da Universidade, Taipa, Macau SAR 999078, China
    Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, Macau SAR 999078, China)

  • Fei Gao

    (Centre for Cognitive and Brain Sciences, University of Macau, Avenida da Universidade, Taipa, Macau SAR 999078, China
    Institute of Modern Languages and Linguistics, Fudan University, Shanghai 200433, China)

Abstract

The COVID-19 outbreak, a recent major public health emergency, was the first national health crisis since China entered the era of mobile social media. In this context, the public posted many quarantine-related posts for help on social media. Most previous studies of social media during the pandemic focused only on people’s emotional needs, with less analysis of quarantine help-seeking content. Based on this situation, this study analyzed the relationship between the number of quarantine help-seeking posts and the number of new diagnoses at different time points in the pandemic using Zhihu, the most comprehensive topic discussion platform in China. It showed a positive correlation between the number of help-seeking posts and the pandemic’s severity. Given the diversity of people’s help-seeking content, this study used topic model analysis and sentiment analysis to explore the key content of people’s quarantine help-seeking posts during the pandemic. In light of the framework of uses and gratifications, we found that people posted the most questions in relation to help with information related to pandemic information and quarantine information. Interestingly, the study also found that the content of people’s quarantine posts during the pandemic was primarily negative in sentiment. This study can thus help the community understand the changes in people’s perceptions, attitudes, and concerns through their reactions to emergencies and then formulate relevant countermeasures to address pandemic control and information regulation, which will have implications for future responses to public health emergencies. Moreover, in terms of psychological aspects, it will help implement future mental health intervention strategies and better address the public’s psychological problems.

Suggested Citation

  • Luanying Li & Lin Hua & Fei Gao, 2022. "What We Ask about When We Ask about Quarantine? Content and Sentiment Analysis on Online Help-Seeking Posts during COVID-19 on a Q&A Platform in China," IJERPH, MDPI, vol. 20(1), pages 1-19, December.
  • Handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:780-:d:1021703
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/20/1/780/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/20/1/780/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhu, Bangren & Zheng, Xinqi & Liu, Haiyan & Li, Jiayang & Wang, Peipei, 2020. "Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Xuehua Han & Juanle Wang & Min Zhang & Xiaojie Wang, 2020. "Using Social Media to Mine and Analyze Public Opinion Related to COVID-19 in China," IJERPH, MDPI, vol. 17(8), pages 1-22, April.
    3. Lucini, Filipe R. & Tonetto, Leandro M. & Fogliatto, Flavio S. & Anzanello, Michel J., 2020. "Text mining approach to explore dimensions of airline customer satisfaction using online customer reviews," Journal of Air Transport Management, Elsevier, vol. 83(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zijing Ye & Ruisi Li & Jing Wu, 2022. "Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment," IJERPH, MDPI, vol. 19(12), pages 1-22, June.
    2. Zvjezdana Gvozdanović & Nikolina Farčić & Hrvoje Šimić & Vikica Buljanović & Lea Gvozdanović & Sven Katalinić & Stana Pačarić & Domagoj Gvozdanović & Željka Dujmić & Blaženka Miškić & Ivana Barać & Na, 2021. "The Impact of Education, COVID-19 and Risk Factors on the Quality of Life in Patients with Type 2 Diabetes," IJERPH, MDPI, vol. 18(5), pages 1-14, February.
    3. Yongqiang Zhao & Liwei Zhang, 2022. "An Advanced Study of Urban Emergency Medical Equipment Logistics Distribution for Different Levels of Urgency Demand," IJERPH, MDPI, vol. 19(18), pages 1-16, September.
    4. Chandra Mahapatra, Subas & Bellamkonda, Raja Shekhar, 2023. "Higher expectations of passengers do really sense: Development and validation a multiple scale-FliQual for air transport service quality," Journal of Retailing and Consumer Services, Elsevier, vol. 70(C).
    5. Christian M. Hafner, 2020. "The Spread of the Covid-19 Pandemic in Time and Space," IJERPH, MDPI, vol. 17(11), pages 1-13, May.
    6. Siqi Lai & Brian Deal, 2022. "Parks, Green Space, and Happiness: A Spatially Specific Sentiment Analysis Using Microblogs in Shanghai, China," Sustainability, MDPI, vol. 15(1), pages 1-18, December.
    7. Fernando Olivares-Delgado & Patricia P. Iglesias-Sánchez & María Teresa Benlloch-Osuna & Carlos de las Heras-Pedrosa & Carmen Jambrino-Maldonado, 2020. "Resilience and Anti-Stress during COVID-19 Isolation in Spain: An Analysis through Audiovisual Spots," IJERPH, MDPI, vol. 17(23), pages 1-23, November.
    8. Ling Lin & Tao Shu & Han Yang & Jun Wang & Jixian Zhou & Yuxuan Wang, 2023. "Consumer-Perceived Risks and Sustainable Development of China’s Online Gaming Market: Analysis Based on Social Media Comments," Sustainability, MDPI, vol. 15(17), pages 1-20, August.
    9. Hainan Huang & Weifan Chen & Tian Xie & Yaoyao Wei & Ziqing Feng & Weijiong Wu, 2021. "The Impact of Individual Behaviors and Governmental Guidance Measures on Pandemic-Triggered Public Sentiment Based on System Dynamics and Cross-Validation," IJERPH, MDPI, vol. 18(8), pages 1-25, April.
    10. Nilashi, Mehrbakhsh & Abumalloh, Rabab Ali & Samad, Sarminah & Alrizq, Mesfer & Alyami, Sultan & Abosaq, Hamad & Alghamdi, Abdullah & Akib, Noor Adelyna Mohammed, 2022. "Factors impacting customer purchase intention of smart home security systems: Social data analysis using machine learning techniques," Technology in Society, Elsevier, vol. 71(C).
    11. Patrick Cheong-Iao Pang & Qixin Cai & Wenjing Jiang & Kin Sun Chan, 2021. "Engagement of Government Social Media on Facebook during the COVID-19 Pandemic in Macao," IJERPH, MDPI, vol. 18(7), pages 1-19, March.
    12. Kumar, Avinash & Chakraborty, Shibashish & Bala, Pradip Kumar, 2023. "Text mining approach to explore determinants of grocery mobile app satisfaction using online customer reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    13. Angela Chang & Xuechang Xian & Matthew Tingchi Liu & Xinshu Zhao, 2022. "Health Communication through Positive and Solidarity Messages Amid the COVID-19 Pandemic: Automated Content Analysis of Facebook Uses," IJERPH, MDPI, vol. 19(10), pages 1-16, May.
    14. Yuye Zhou & Jiangang Xu & Maosen Yin & Jun Zeng & Haolin Ming & Yiwen Wang, 2022. "Spatial-Temporal Pattern Evolution of Public Sentiment Responses to the COVID-19 Pandemic in Small Cities of China: A Case Study Based on Social Media Data Analysis," IJERPH, MDPI, vol. 19(18), pages 1-18, September.
    15. Iustina Alina Boitan & Emilia Mioara Campeanu & Sanja Sever Malis, 2021. "Economic Sentiment Perceptions During COVID-19 Pandemic – A European Cross-Country Impact Assessment," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(Special15), pages 982-982, November.
    16. Babak Naysary & Mehdi Malekzadeh & Ruth Tacneng & Amine Tarazi, 2022. "Big data analytics application in multi-criteria decision making: the case of eWallet adoption," Working Papers hal-03632834, HAL.
    17. Zha, Wenbin & Ye, Qian & Li, Jian & Ozbay, Kaan, 2023. "A social media Data-Driven analysis for transport policy response to the COVID-19 pandemic outbreak in Wuhan, China," Transportation Research Part A: Policy and Practice, Elsevier, vol. 172(C).
    18. Park, Jeongeun & Yang, Donguk & Kim, Ha Young, 2023. "Text mining-based four-step framework for smart speaker product improvement and sales planning," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    19. Schmalz, Ulrike & Ringbeck, Jürgen & Spinler, Stefan, 2021. "Door-to-door air travel: Exploring trends in corporate reports using text classification models," Technological Forecasting and Social Change, Elsevier, vol. 170(C).
    20. Pereira, Francisco & Costa, Joana Martinho & Ramos, Ricardo & Raimundo, António, 2023. "The impact of the COVID-19 pandemic on airlines’ passenger satisfaction," Journal of Air Transport Management, Elsevier, vol. 112(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:20:y:2022:i:1:p:780-:d:1021703. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.