This is part of the SafeBnB project that is developed during Hack the North 2018 @ University of Waterloo. This project focus on analyzing public available AirBnb listsings and review data in Toronto area with Toronto Police Deparment crimes dataset.
The goal is to map crimes occurances near different airbnb listings, quantifing those corelations as "safety index" to determine the safety level of that specific airbnb and serve as the model for the project. Also, apply NLP on reviews data we can get somewhat meaningful insights from the previous customers.
The following datasets are used: Toronto police MCI (major crimes index) dataset 2014-17 Toronto police Homicide dataset 2014-2017 Open data Airbnb listings/reviews datasets
The web app shows Airbnb listings for areas searched for by the user and presents them in decreasing order based on a safety index. The safety index was determined by analyzing publicly available crime data for Toronto over an extended time period and the presence of certain keywords like "safe, quiet, scary" in reviews that indicated safety or lack of safety in the Airbnb's area.
See Devpost Page[https://devpost.com/software/safe-airbnb] for details.