Quantifying Urban Social Well-Being using Mobile Phone Data

Gundogdu, Didem (2018) Quantifying Urban Social Well-Being using Mobile Phone Data. PhD thesis, University of Trento.

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Today, more than half of the world population is living in cities, which has been doubled in the last 50 years. The reason for that attraction is not only economical, but also security, education, and health. While people migrate to cities to reach improved life conditions, several issues raised by the increasing population. Recent studies have shown the importance of ethnic and cultural diversity of urban population to encourage tolerance, and to foster creativity and economic growth. Facing the urban growth challenges, we search for the key formulas to obtain healthy societies under the light of new type of data sources, such as mobile phone usage datasets. To this end, first we build up a tool to identify security related incidents from a country, which unstable political conditions held. Then we trace the formulas of healthy societies with examples from both developing and developed countries. We check the individual interaction and communication pattern effects (bridging and bonding) for the existence of social capital. Then we analyze aggregated ethnic diversity, and associate segregation scores with census data, and different ethnic groups preferences to move in the city, existence of any pattern for specific nation. The current studies are mainly hypothetical, with the absence of large scale real life data sources. This thesis aims to provide an insight to policy makers for building healthy societies, for the benefit of urban well-being.

Item Type:Doctoral Thesis (PhD)
Doctoral School:Information and Communication Technology
PhD Cycle:30
Subjects:Area 01 - Scienze matematiche e informatiche > INF/01 INFORMATICA
Area 13 - Scienze economiche e statistiche > SECS-S/05 STATISTICA SOCIALE
Uncontrolled Keywords:social capital, complex networks, segregation, economic well-being, mobile phone datasets, call detail records
Funders:Fondazione Bruno Kessler
Repository Staff approval on:19 Apr 2018 09:22

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