Online profiling of volunteers in public health emergencies: insights from COVID-19 in China

Abstract Background During public health emergencies, the diverse backgrounds of volunteers pose numerous management challenges. This study aims to develop an online profiling model of volunteers using social media data to achieve a more comprehensive and objective understanding of them. Methods In...

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Main Authors: Hongzhou Shen, Qirui Chen, Changcheng Li
Format: Article
Language:English
Published: BMC 2025-01-01
Series:BMC Public Health
Subjects:
Online Access:https://doi.org/10.1186/s12889-025-21446-8
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author Hongzhou Shen
Qirui Chen
Changcheng Li
author_facet Hongzhou Shen
Qirui Chen
Changcheng Li
author_sort Hongzhou Shen
collection DOAJ
description Abstract Background During public health emergencies, the diverse backgrounds of volunteers pose numerous management challenges. This study aims to develop an online profiling model of volunteers using social media data to achieve a more comprehensive and objective understanding of them. Methods In the proposed model, the study designed five profiling tags: basic information, sentiment, topic features, interest preferences, and online social engagement. K-Modes clustering was employed to implement the profiling. To validate the feasibility of the model, an empirical study was conducted using Weibo data from 1,070 volunteers during the COVID-19 pandemic in China, resulting in the online profiling of these volunteers. Results Four categories of volunteers could be identified: Public Affairs Pioneers (32.4%), Diary Record Lurkers (32.8%), Social Topic Sharers (20.9%), and Fashion and Entertainment Influencers (13.9%). Overall, volunteers were predominantly female, generally interested in entertainment, relatively satisfied with their volunteer work, and possessed a sense of social responsibility. The four categories of volunteers exhibited distinct characteristics in terms of interests, online social behavior, and influence. Conclusions The proposed online profiling model objectively captures the characteristics of volunteers during public health emergencies. The four volunteer categories identified through the empirical results provide a multidimensional and comprehensive understanding of volunteers. For different volunteer categories, official agencies can tailor their recruitment, management, and training strategies to better suit the specific needs and strengths of the volunteers, thereby enhancing the effectiveness and efficiency of volunteer engagement and ensuring volunteers are well-prepared and supported in their roles.
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spelling doaj-art-bf30a380bc6a4f0b8efcddd44c0100b72025-01-26T12:55:36ZengBMCBMC Public Health1471-24582025-01-0125111910.1186/s12889-025-21446-8Online profiling of volunteers in public health emergencies: insights from COVID-19 in ChinaHongzhou Shen0Qirui Chen1Changcheng Li2School of Management, Nanjing University of Posts and TelecommunicationsSchool of Management, Nanjing University of Posts and TelecommunicationsSchool of Management, Nanjing University of Posts and TelecommunicationsAbstract Background During public health emergencies, the diverse backgrounds of volunteers pose numerous management challenges. This study aims to develop an online profiling model of volunteers using social media data to achieve a more comprehensive and objective understanding of them. Methods In the proposed model, the study designed five profiling tags: basic information, sentiment, topic features, interest preferences, and online social engagement. K-Modes clustering was employed to implement the profiling. To validate the feasibility of the model, an empirical study was conducted using Weibo data from 1,070 volunteers during the COVID-19 pandemic in China, resulting in the online profiling of these volunteers. Results Four categories of volunteers could be identified: Public Affairs Pioneers (32.4%), Diary Record Lurkers (32.8%), Social Topic Sharers (20.9%), and Fashion and Entertainment Influencers (13.9%). Overall, volunteers were predominantly female, generally interested in entertainment, relatively satisfied with their volunteer work, and possessed a sense of social responsibility. The four categories of volunteers exhibited distinct characteristics in terms of interests, online social behavior, and influence. Conclusions The proposed online profiling model objectively captures the characteristics of volunteers during public health emergencies. The four volunteer categories identified through the empirical results provide a multidimensional and comprehensive understanding of volunteers. For different volunteer categories, official agencies can tailor their recruitment, management, and training strategies to better suit the specific needs and strengths of the volunteers, thereby enhancing the effectiveness and efficiency of volunteer engagement and ensuring volunteers are well-prepared and supported in their roles.https://doi.org/10.1186/s12889-025-21446-8Public health emergenciesVolunteersOnline profilingSocial mediaCOVID-19Weibo
spellingShingle Hongzhou Shen
Qirui Chen
Changcheng Li
Online profiling of volunteers in public health emergencies: insights from COVID-19 in China
BMC Public Health
Public health emergencies
Volunteers
Online profiling
Social media
COVID-19
Weibo
title Online profiling of volunteers in public health emergencies: insights from COVID-19 in China
title_full Online profiling of volunteers in public health emergencies: insights from COVID-19 in China
title_fullStr Online profiling of volunteers in public health emergencies: insights from COVID-19 in China
title_full_unstemmed Online profiling of volunteers in public health emergencies: insights from COVID-19 in China
title_short Online profiling of volunteers in public health emergencies: insights from COVID-19 in China
title_sort online profiling of volunteers in public health emergencies insights from covid 19 in china
topic Public health emergencies
Volunteers
Online profiling
Social media
COVID-19
Weibo
url https://doi.org/10.1186/s12889-025-21446-8
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AT changchengli onlineprofilingofvolunteersinpublichealthemergenciesinsightsfromcovid19inchina