Investigating individual traits, network dynamics and economic behavior using mobile phone data

Centellegher, Simone (2019) Investigating individual traits, network dynamics and economic behavior using mobile phone data. PhD thesis, University of Trento.

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Recent years have witnessed a growing interest in analyzing the huge amount of human behavioral data generated by new technologies such as mobile phones, social media and credit cards. These technologies leave a trail of "digital breadcrumbs" that allow us to have new quantitative insights that may reveal patterns of individual and group behaviors. Moreover, it allows us to better understand human behavior at a fine-grained resolution and for periods of time that were previously inconceivable. Researchers can now observe human behavior, ask research questions and run experiments in ways that were simply impossible in the recent past due to qualitative methods that, despite their undeniable benefits, proved to be time and resource consuming and therefore difficult to apply to large scale studies. Studying social interaction and social networks extracted from these data sources, allow us to understand not only individual behaviors and their characteristics, but also to observe the relationships between individuals, the structure, the content and their dynamics over long periods of time. Given the capacity of mobile phones to capture real observations of communications between people, we took advantage of the data collected from these devices to further explore and investigate human behavior. Specifically, in this dissertation, we (i) present the Mobile Territorial Lab (MTL) project and illustrate the advantages of using a living lab approach to collect a longitudinal set of data from a target group of parents; (ii) investigate how the personality dispositions of an individual influence how (s)he manages her/his social network; (iii) investigate whether and how the behavior of an individual as sensed through her/his mobile phone behavior is related to the future adoption and use of the leading mobile money service M-Pesa.

Item Type:Doctoral Thesis (PhD)
Doctoral School:Information and Communication Technology
PhD Cycle:31
Subjects:Area 01 - Scienze matematiche e informatiche > INF/01 INFORMATICA
Uncontrolled Keywords:human behavior understanding, call detail records, mobile money, personality traits, social networks
Funders:Fondazione Bruno Kessler
Repository Staff approval on:19 Apr 2019 13:05

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