Theory Session:
- 8:30 - 9:30 - Bruno Gonçalves - We will start with an overview of geolocated APIs such as those of Twitter and Foursquare, using Python focusing on their similarities and differences. Applications covered will range from visualizing Twitter usage and language geography , Inter-City Mobility through airline connections and the Global Language Network.
- 9:30 - 10:30 - Anastasios Noulas - In this part of the tutorial attendees will be provided with an overview perspective on location-based technologies with a focus on urban applications. From human mobility models and theory, to neighborhood detection and finding an appropriate location for placing a shop or amenity attendees will be introduced to the mechanics and building blocks of a number of research works with a strong application orientation. Next, the spotlight will be put on newer advancements in the area of the so-call gig economy, introducing services like Uber and Airbnb, highlighting opportunities for research using corresponding transport and hospitality datasets.
- 10:30 - 11:00 Coffee break
- 11:00 - 12:00 - Desislava Hristova - Overview of the theory of social capital in cities and the social role of places. This will include an introduction to structural holes and open network structures in light of social capital and how this can be extended to places in cities. The role of social media will be discussed as a proxy for understanding urban development and gentrification in cities like London and New York. Concrete examples of measuring the digital footprints of wellbeing in cities and beyond will be provided alongside the theory of cultural capital and urban development.
- 12:00 - 13:30 - Lunch
Practical Session:
- 13:30 - 14:30 - Bruno Gonçalves - After an introduction on how to collect data using the Twitter and Foursquare APIs we will proceed to perform several simple analyses to illustrate different important techniques and libraries. Using the airline transportation network (from the Bureau of Transportation Statistics) as a starting point, we will build a simple model of large scale mobility within the United States.
- 14:30 - 15:30 - Anastasios Noulas - In this part of the tutorial Anastasios will first focus on foundational methods for spatial retrieval using Python. Code snippets that allow for the organisation of spatial data, the calculation of geographic distances as well as the retrieval of points within a radius, given a pair of coordinates, will be examined in detail. Next, the Networkx library will be employed for the analysis of networks of places, whereas the session will close with a demo showcase of Uber's deck.gl framework for visualisation of spatial data.
- 15:30 - 16:00 Coffee break
- 16:00 - 17:00 - Desislava Hristova - Understanding Urban Development and Gentrification from Social Media. Social media is notoriously biased towards tech-savvy younger populations but can we exploit this bias to better understand processes of gentrification and predict urban development in neighbourhoods? We will look at geo-social data from Twitter and Foursquare alongside public data about deprivation in neighbourhoods to understand the contradictions which arise when complex urban processes such as gentrification take place. The role of symbolic capital such as social and cultural capital and the different ways of quantifying it will be explored as a follow-up to their theoretical definition in the first part of the tutorial. This will include hands-on exploration of predicting housing prices in developing neighbourhoods using standard statistical methods in Python.
The tutorial will take place on May 15.