Social-Media aided Hyperlocal Help-Network Matching Routing during Emergencies

摘要

Catering to the humanitarian needs of hurricane-affected residents is the most challenging part for the emergency management agencies. These agencies typically follow a centralized help disbursement model by collecting donations and disbursing them to the needful through their employees or registered volunteers. The time required to move goods and volunteers to the place of need poses a survival challenge to emergency hit residents especially during the initial few days after the emergency. We propose and design a social-media (specifically Twitter) aided hyperlocal help-network by utilizing the tweets to identify users who require help and those who are willing to provide it. We also analyze tweets related to road damage, traffic jam, etc. to sense the current state of road infrastructure. We propose to match the help seekers and those who are willing to help, taking into consideration their spatial proximity and then provide the fastest working route for the help-provider to reach the matched help-seeker. Numerical experiments performed on hurricane Sandy Twitter dataset shows the effectiveness of the proposed approach as we are able to satisfy the need of more than 80% of help-seekers by matching them to appropriate help-offerer within a 24-hour duration after posting the request for help tweet with a maximum travel distance of 10 km.