Abstract
Understanding attention dynamics on social media during pandemics could help governments minimize the effects. We focus on how COVID-19 has influenced the attention dynamics on the biggest Chinese microblogging website Sina Weibo during the first four months of the pandemic. We study the real-time Hot Search List (HSL), which provides the ranking of the most popular 50 hashtags based on the amount of Sina Weibo searches. We show how the specific events, measures and developments during the epidemic affected the emergence of different kinds of hashtags and the ranking on the HSL. A significant increase of COVID-19 related hashtags started to occur on HSL around January 20, 2020, when the transmission of the disease between humans was announced. Then very rapidly a situation was reached where COVID-related hashtags occupied 30–70% of the HSL, however, with changing content. We give an analysis of how the hashtag topics changed during the investigated time span and conclude that there are three periods separated by February 12 and March 12. In period 1, we see strong topical correlations and clustering of hashtags; in period 2, the correlations are weakened, without clustering pattern; in period 3, we see a potential of clustering while not as strong as in period 1. We further explore the dynamics of HSL by measuring the ranking dynamics and the lifetimes of hashtags on the list. This way we can obtain information about the decay of attention, which is important for decisions about the temporal placement of governmental measures to achieve permanent awareness. Furthermore, our observations indicate abnormally higher rank diversity in the top 15 ranks on HSL due to the COVID-19 related hashtags, revealing the possibility of algorithmic intervention from the platform provider.
Highlights
In our times of information deluge the dynamics of public attention is of eminent importance from many aspects, including education, politics, marketing and governance
As the first death case occurred on January 11, second one occurred on Hot Search List (HSL) on January 16 and more infected cases detected in other cities in China as well as in the surrounding Asian countries, rumours and scared emotions about the unknown pneumonia were permeating in the society and the number of daily COVID-related hashtags started to increase rapidly on January 19
4 Discussion and summary In this work, we have studied the public attention dynamics on the real-time Hot Search List (HSL) of the biggest Chinese microblogging website Sina Weibo under the influence of the COVID-19 pandemic
Summary
In our times of information deluge the dynamics of public attention is of eminent importance from many aspects, including education, politics, marketing and governance. At the same time these media provide unprecedented possibilities to study attention dynamics [1, 2] as they produce Big Data open for inves-. The microblogging service Twitter [3] is suited to provide the basis for quantitative studies on the dynamics of public attention as the content of the messages is available [4]. Twitter data have served as the basis of modelling attention dynamics during pre-election time [7] or studying the relationship between public attention and social emotions [8]
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.