Open Access
ARTICLE
What is Discussed about COVID-19: A Multi-Modal Framework for Analyzing Microblogs from Sina Weibo without Human Labeling
Hengyang Lu1, *, Yutong Lou2, Bin Jin2, Ming Xu2
1 School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, 214122, China.
2 National Key Laboratory for Novel Software Technology, Department of Computer Science and Technology, Nanjing University, Nanjing, 210023, China.
* Corresponding Author: Hengyang Lu. Email: .
(This article belongs to the Special Issue: Artificial Intelligence and Information Technologies for COVID-19)
Computers, Materials & Continua 2020, 64(3), 1453-1471. https://doi.org/10.32604/cmc.2020.011270
Received 29 April 2020; Accepted 23 May 2020; Issue published 30 June 2020
Abstract
Starting from late 2019, the new coronavirus disease (COVID-19) has become
a global crisis. With the development of online social media, people prefer to express
their opinions and discuss the latest news online. We have witnessed the positive
influence of online social media, which helped citizens and governments track the
development of this pandemic in time. It is necessary to apply artificial intelligence (AI) techniques to online social media and automatically discover and track public opinions
posted online. In this paper, we take Sina Weibo, the most widely used online social
media in China, for analysis and experiments. We collect multi-modal microblogs about
COVID-19 from 2020/1/1 to 2020/3/31 with a web crawler, including texts and images
posted by users. In order to effectively discover what is being discussed about COVID-19
without human labeling, we propose a unified multi-modal framework, including an
unsupervised short-text topic model to discover and track bursty topics, and a selfsupervised model to learn image features so that we can retrieve related images about
COVID-19. Experimental results have shown the effectiveness and superiority of the
proposed models, and also have shown the considerable application prospects for
analyzing and tracking public opinions about COVID-19.
Keywords
Cite This Article
APA Style
Lu, H., Lou, Y., Jin, B., Xu, M. (2020). What is discussed about COVID-19: A multi-modal framework for analyzing microblogs from sina weibo without human labeling. Computers, Materials & Continua, 64(3), 1453-1471. https://doi.org/10.32604/cmc.2020.011270
Vancouver Style
Lu H, Lou Y, Jin B, Xu M. What is discussed about COVID-19: A multi-modal framework for analyzing microblogs from sina weibo without human labeling. Comput Mater Contin. 2020;64(3):1453-1471 https://doi.org/10.32604/cmc.2020.011270
IEEE Style
H. Lu, Y. Lou, B. Jin, and M. Xu "What is Discussed about COVID-19: A Multi-Modal Framework for Analyzing Microblogs from Sina Weibo without Human Labeling," Comput. Mater. Contin., vol. 64, no. 3, pp. 1453-1471. 2020. https://doi.org/10.32604/cmc.2020.011270
Citations