  Social media platforms, such as Twitter, have been increasingly used by
people during natural disasters to share information and request for help.
Hurricane Harvey was a category 4 hurricane that devastated Houston, Texas, USA
in August 2017 and caused catastrophic flooding in the Houston metropolitan
area. Hurricane Harvey also witnessed the widespread use of social media by the
general public in response to this major disaster, and geographic locations are
key information pieces described in many of the social media messages. A
geoparsing system, or a geoparser, can be utilized to automatically extract and
locate the described locations, which can help first responders reach the
people in need. While a number of geoparsers have already been developed, it is
unclear how effective they are in recognizing and geo-locating the locations
described by people during natural disasters. To fill this gap, this work seeks
to understand how people describe locations during a natural disaster by
analyzing a sample of tweets posted during Hurricane Harvey. We then identify
the limitations of existing geoparsers in processing these tweets, and discuss
possible approaches to overcoming these limitations.
