AUTHOR=Yin Ruheng , Wu Jing , Tian Rui , Gan Feng 

TITLE=Topic modeling and sentiment analysis of Chinese people’s attitudes toward volunteerism amid the COVID-19 pandemic

JOURNAL=Frontiers in Psychology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.1064372

DOI=10.3389/fpsyg.2022.1064372

ISSN=1664-1078

ABSTRACT=The COVID-19 pandemic has created an urgent need for volunteers to complement overwhelmed public health systems. This study aims to explore Chinese people’s attitudes towards volunteerism amid the COVID-19 pandemic. To this end, we identify the latent topics in volunteerism-related microblogs on Weibo, the Chinese equivalent of Twitter using the topic modeling analysis via Latent Dirichlet Allocation (LDA). To further investigate the public sentiment towards the topics generated by LDA, we also conducted sentiment analysis on the sample posts using the open-source natural language processing (NLP) technique from Baidu. Through an in-depth analysis of 91,933 Weibo posts, this study captures ten topics that are, in turn, distributed into five factors associated with volunteerism in China as motive fulfillment (n= 31,661, 34.44%), fear of COVID-19 (n= 22,597, 24.58%), individual characteristic (n= 17,688, 19.24%), government support (n= 15,482, 16.84%), and community effect (n= 4505, 4.90%). The results show that motive fulfillment, government support, and community effect are the factors that could enhance positive attitudes towards volunteerism since the topics related to these factors report high proportions of positive emotion. Fear of COVID-19 and individual characteristic are the factors inducing negative sentiment towards volunteerism as the topics related to these factors show relatively high proportions of negative emotion. The provision of tailored strategies based on the factors could potentially enhance Chinese people’s willingness to participate in volunteer activities during the COVID-19 pandemic.