@inproceedings{21aaad35fcf143c1a6af9dba095ad9b1,
title = "Public Reaction on Social Media During COVID-19: A Comparison Between Twitter and Weibo",
abstract = "COVID-19 has been spreading across the world starting from early 2020, and there are numerous and varied discussions on social media platforms related to the COVID-19 outbreak. In this study, we analyzed and compared the data on Twitter and Weibo at different times based on the public{\textquoteright}s understanding of COVID-19 to ultimately understand the characteristics of social media reaction in U.S. and in China during the pandemic. Results show that both similarities and differences existed when comparing the public reaction on social media in the U.S. and in China. The study suggests that data from social media could be used as a good reflection of the public{\textquoteright}s reaction, especially in a pandemic like COVID-19. It is important for the government to understand people{\textquoteright}s timely reaction during the pandemic in order to ensure the authorities are on the right direction to provide services and accurate information to the public.",
keywords = "Data analytics, Social media, Social response, COVID-19",
author = "Tian Wang and Ian Brooks and Masooda Bashir",
note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; Computing Conference, 2021 ; Conference date: 15-07-2021 Through 16-07-2021",
year = "2022",
doi = "10.1007/978-3-030-80119-9_38",
language = "English (US)",
isbn = "9783030801182",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer",
pages = "612--625",
editor = "Kohei Arai",
booktitle = "Intelligent Computing - Proceedings of the 2021 Computing Conference",
address = "Germany",
}