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...
Saved in:
| Main Authors: | , , |
|---|---|
| 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 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832585312849625088 |
|---|---|
| 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. |
| format | Article |
| id | doaj-art-bf30a380bc6a4f0b8efcddd44c0100b7 |
| institution | Kabale University |
| issn | 1471-2458 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Public Health |
| 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 |
| 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 |
| url | https://doi.org/10.1186/s12889-025-21446-8 |
| work_keys_str_mv | AT hongzhoushen onlineprofilingofvolunteersinpublichealthemergenciesinsightsfromcovid19inchina AT qiruichen onlineprofilingofvolunteersinpublichealthemergenciesinsightsfromcovid19inchina AT changchengli onlineprofilingofvolunteersinpublichealthemergenciesinsightsfromcovid19inchina |