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Title: Applications of new forms of data to demographics
Author: Leak, A. B.
ISNI:       0000 0004 7228 4110
Awarding Body: UCL (University College London)
Current Institution: University College London (University of London)
Date of Award: 2017
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At the outset, this thesis sets out to address limitations in conventional population data for the representation of stocks and flows of human populations. Until now, many of the data available for studying population behaviour have been static in nature, often collected on an infrequent basis or in an inconsistent manner. However, rapid expansion in the use of online technologies has led to the generation of a huge volume of data as a byproduct of individuals’ online activities. This thesis sets out to exploit just one of these new data channels: raw geographically referenced messages collected by the Twitter Online Social Network. The thesis develops a framework for the creation of functional population inventories from Twitter. Through the application of various data mining and heuristic techniques, individual Twitter users are attributed with key demographic markers including age, gender, ethnicity and place of residence. However, while these inventories possess the required data structure for analysis, little is understood about whom they represent and for what purposes they may be reliably employed. Thus a primary focus of this thesis is the assessment of Twitter-based population inventories at a range of spatial scales from the local to the global. More specifically, the assessment considers issues of age, gender, ethnicity, geographic distribution and surname composition. The value of such rich data is demonstrated in the final chapter in which a detailed analysis of the stocks and flows of peoples within the four largest London airports is undertaken. The analysis demonstrates both the extraction of conventional insight, such as passenger statistics and new insights such as footfall and sentiment. The thesis concludes with recommendations for the ways in which social media analysis may be used in demographics to supplement the analysis of populations using conventional sources of data.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available