Hello everyone,
my name is Wenjie from the Hong Kong University of Science and Technology.
Today I'm excited to present our work
titled how to save lives with microblogs? lessons from the usage of Weibo for requests
for medical assistance during covid-19. In large scale crisis such as floods and epidemics,
local emergency services sometimes fail to provide timely and adequate assistance
to the affected population due to limited bandwidth and resources.
For example, during Hurricane Harvey in 2017, the 911 system in Houston was
overwhelmed by thousands of calls, leaving many in need unanswered.
Similarly, when COVID-19 broke out in Wuhan, China.
The medical system was overburdened by the huge increase of infected patients.
Due to the widened gap between the need and available medical resources,
especially hospital beds, many patients couldn't get timely care.
When the local community doesn't provide enough support, some people turn to seek
help through social media such as Twitter, Weibo and other microblogging platforms.
Microblogging services offers functions such as posting hashtags and geotags
that allows help seekers to send requests like rescue operations or
emergency medical care to a broader audience.
During the last few years,
people around the world have used microblogging for help seeking when facing
crisis, such as flood, heavy rains and the recent COVID-19 pandemic.
There are many successful cases
in that people received assistance through this channel.
Despite this common practice,
it is unclear whether microblogging is effective enough for supporting help
seeking in an emergency, and if not, what aspects need to be improved.
Such an understanding is crucial because it can inform better microblogging designs
for use in emergency situations, thereby increasing the chance of saving lives.
To fill this gap,
we conducted a case study examining the phenomenon of COVID-19 patients seeking
medical assistance on Weibo, the biggest microblogging site in China.
Our research context lies in the early stage of COVID-19.
Between January and March 2020,
when Wuhan's health care system collapsed, many infected citizens and suspected
patients turned to Weibo to ask for help such as hospitalization. Weibo
then launched a special online community called
#COVID-19 Patients seek help [Super Topic]#, in short,
the help seeking super topic, for accommodating these requests.
Basically, the super topic feature is a subreddit-like community that allows
members to discuss a specific topic and allow administrators to set up
community specific rules for management. For help seeking
super-topic, two key rules were settled.
First, posts must be help requests.
Second, a help request must follow a structured template containing
information like name, phone number, symptom descriptions, etc.
Posts that don't follow the rules will be deleted.
This helps seeking phenomenon soon gained attention from online volunteers.
They respond by collecting and verifying
requests from inside and outside the community and then coordinating
with local authorities and non-governmental organizations to provide onsite assistance.
Over 3000 cases have been submitted
to the local government, and at least 318 people have received assistance.
In this paper,
we are particularly interested in how people used the help seeking social topic
and other microblogging functions to seek medical assistance on Weibo.
Specifically, we ask the following two research questions.
First, what microblogging functions were
used for help seeking and how effective is it for this purpose?
Second, how did COVID-19 patients use
microblogging functions to seek assistance?
Before answering these questions,
we need to collect COVID-19 help requests across the entire Weibo platform.
This was done using an NLP based method.
We first created a training set of 2000 post by sampling posts from the help
seeking super-topic and other locations on Weibo.
Then we trained a BERT binary classifier
to predict whether a post contains COVID-19 help seeking messages or not.
This model achieved over 95% accuracy and F1.
After that, we applied the model to a dataset
of over 100 million Weibo posts from January to May 2020.
Some gathered by our crawlers, others from open-source data.
In the end, we identify 8000 help requests related to the Covid-19 cases.
With the data,
we explored RQ1 by performing a content analysis to find microblogging features
used for help seeking and summarized their affordances and limitations.
In RQ2, we analyzed the trends of function usage in help requests
and conducted a controlled, interrupted time series analysis to see if
people changed the way they used microblogging features to seek help.
In total, our analysis identified 9 microblogging functions used for help
seeking like super-topics, posting, quoting, et cetera.
Among them, the help seeking super topic and regular posting are the most commonly
used features, accounting for around 95% of usage.
In practice, super topics support help
seeking better than regular posting because the two rules of help seeking
community enable the request easier to identify, receive retweets,
and manage by help providers than those posted on personal timelines.
In addition, we identified four limitations of using
microblogging for help seeking during crisis, including the capability of search
and track help request, ease of use, and Privacy protection.
For example, the current functions do not
track assistance progress for help seekers, which may lead to some expired message
being retweeted and wasting public resources.
We also found many people use the help seeking topic and mention function
incorrectly and fail to maximize their exposure and the chance of receiving help.
This may be due to the difficulties of using or distinguishing these features.
As for RQ2,
our classifier find that there were already a lot of help requests made
by regular posting before the help seeking super topic was created.
Our statistic analysis found that despite the super topic gradually gaining public
attention and hitting the trending list on February 3, the usage of regular
posting function did not decrease significantly, meaning that help seekers
did not make a significant switch to the super topic,
though it is a more effective channel for help seeking, as previously mentioned.
In conclusion, our study suggests a centralized,
managed channel is better for help seeking than basic microblogging features because
it allows more effective communication between help seekers and help providers.
However, we also argue that designers should be aware of the trade off between
developing new technologies or using existing ones for crisis communication.
Since our findings suggest that users may
struggle to adapt to such emerging technologies during emergency situations.
In addition, our work also points out that existing microblogging services have
4 limitations that must be addressed when used for help seeking.
Our work suggests some design considerations accordingly.
For instance, to make functions easier
to use, microblogging system can detect if users are editing a help request
and suggest better functions that's all for our papers.
Thank you.