  Posting help-seeking requests on social media has been broadly adopted by
victims during natural disasters to look for urgent rescue and supplies. The
help-seeking requests need to get sufficient public attention and be promptly
routed to the intended target(s) for timely responses. However, the huge volume
and diverse types of crisis-related posts on social media might limit
help-seeking requests to receive adequate engagement and lead to their
overwhelm. To understand this problem, this work proposes a mixed-methods
approach to figure out the overwhelm situation of help-seeking requests, and
individuals' and online communities' strategies to cope. We focused on the 2021
Henan Floods in China and collected 141,674 help-seeking posts with the keyword
"Henan Rainstorm Mutual Aid" on a popular Chinese social media platform Weibo.
The findings indicate that help-seeking posts confront critical challenges of
both external overwhelm (i.e., an enormous number of non-help-seeking posts
with the help-seeking-related keyword distracting public attention) and
internal overwhelm (i.e., attention inequality with 5% help-seeking posts
receiving more than 95% likes, comments, and shares). We discover linguistic
and non-linguistic help-seeking strategies that could help to prevent the
overwhelm, such as including contact information, disclosing situational
vulnerabilities, using subjective narratives, and structuring help-seeking
posts to a normalized syntax. We also illustrate how community members
spontaneously work to prevent the overwhelm with their collective wisdom (e.g.,
norm development through discussion) and collaborative work (e.g.,
cross-community support). We reflect on how the findings enrich the literature
in crisis informatics and raise design implications that facilitate effective
help-seeking on social media during natural disasters.
