Following a disaster, millions and millions of communications, either directly or via Twitter and Facebook, are sent right when disaster response organizations have the least capacity to filter and pull out the messages that have higher priority. Bystanders often post about what is happening and create an influx of information on social media faster and more informative than news reports. However, often only one in every thousand of those messages has actual relevant content to the disaster response professionals to act upon.
Disaster message classification represents a significant challenge for resource distribution:
Since its establishment in 2008, Airbnb has been offering tourists a unique way to find short and long-term homestay accommodations when traveling. As part of the Airbnb Inside initiative, the Boston Airbnb Listing dataset describes the listing activities of properties in Boston, MA.
Here, I will analyze the Airbnb Boston Listings dataset from here, which includes around 130 descriptions of amenities, location, and price for each listing.
Aside from the Listings, Airbnb Inside offers two other types of dataset:
The original Airbnb datasets can be found here.