The project is based on the analysis of data corresponding to the cities of Barcelona, ??Copenhagen, Melbourne, Paris, cities among the first in the world for having more tourists.

Today, Apps like Tripadvisor and Airbnb, contain relevant information from each city that helps to understand economic and social dynamics. The objective of this project is to extract that information, geolocate it and thus be able to generate conclusions based on indicators such as restaurant distribution (Tripadvisor) which are important tourist attractors, Distribution of rooms for rent (Airbnb), from which prices can also be analyzed , type of room and the profile of the tenant.

How?

Using Python and the Scrapin tool, the information was extracted from Tripadvisor, and then using Qgis, the distribution of the restaurants registered in these cities was geolocated.

Then, this information is superimposed on the data extracted from Airbnb open Data, geolocated in Qgis to compare and generate a route between the areas where tourists rent rooms (which are mostly Airbnb users) and the places that usually attend.

Copenhagen Prices Heatmap

Paris Prices Heatmap

Melbourne Prices Heatmap

Barcelona Prices Heatmap

Finally, with Open Airbnb data, using Python, the quantity and frequency with which apartments are rented in the four cities, the type of room, is analyzed.

‘”Tripadvisor & Airbnb overlay and analysis”’ is a project of IaaC, Institute for Advanced Architecture of Catalonia developed at Master in City & Technology in (2019/2020) by:
Students: Eli Munn, Linara Salikhova, Rovianne Santiago and Michelle Rodríguez

Faculty: Diego Pajarito