Year: 2020
Type: conference-paper
Abstract: Cities are complex systems and understanding their structure is critical for multiple applications. However, traditional urban planning is challenged by the dynamics of the urban system. Fortunately, in recent years, multiple datasets reflecting human activity in nearly real-time have become available. This paper leverages geo-tagged VKontakte and Google Places social media data for building three different networks between locations across Saint-Petersburg and revealing the structure of the city through the community structure of those networks. Comparative analysis of the discovered network structure and its ability to capture meaningful socio-economic patterns across the city is evaluated. Results will aid urban, transportation, infrastructural planning, policy-making, real estate and socio-economic development initiatives.
Source: Procedia Computer Science
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W3111079810