  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.
