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Title: Estimating social networks using communications metadata gathered from mobile devices
Author: Banford, Jamie A.
ISNI:       0000 0004 2740 2093
Awarding Body: University of Strathclyde
Current Institution: University of Strathclyde
Date of Award: 2011
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Mobile communication devices are now truly ubiquitous; they are present everywhere in the modern world. They are also the first human artefacts capable of automatically detecting the subtle ways in which people reveal the nature of the relationships between them. This information is contained within the communications metadata available on these devices. By analysing these communications metadata certain tie signs become discernible and it becomes possible to estimate the current state of the social relationships of the user of the device. However, although this information is available on mobile communication devices few established techniques for gathering, and interpreting it have been defined. This thesis presents empirical investigations into detecting and categorising social relationships using mobile devices. It introduces mechanisms to detect the social ties between the users of mobile devices, based on the interactions between them, and explores techniques to accurately categorise these ties. The ability to detect social ties allows the construction of a social graph with out any prior knowledge of the social relationships between the users of mobile devices. The results of the investigations reported in this thesis show that, although large amounts of data are lost while gathering social social data using mobile devices, estimated ties are confirmed to be correct in the majority of cases.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available