<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-09-18T21:12:14Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/98631" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/98631</identifier><datestamp>2026-06-17T14:43:25Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131022</setSpec></header><metadata><dim:dim xmlns:dim="http://www.dspace.org/xmlns/dspace/dim" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://www.dspace.org/xmlns/dspace/dim http://www.dspace.org/schema/dim.xsd">
   <dim:field mdschema="dc" element="contributor" qualifier="advisor" lang="en_US">Marta C. Gonzàlez, Joseph M. Sussman and P. Christopher Zegras.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Toole, Jameson Lawrence</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="other" lang="en_US">Massachusetts Institute of Technology. Engineering Systems Division.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department">Massachusetts Institute of Technology. Engineering Systems Division</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2015-09-17T19:00:56Z</dim:field>
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   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2015</dim:field>
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   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: Ph. D., Massachusetts Institute of Technology, Engineering Systems Division, June 2015.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis. "February 2015."</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 223-241).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">According the United Nations Population Fund (UNFPA), 2008 marked the first year in which the majority of the planet's population lived in cities. Urbanization, already over 80% in many western regions, is increasing rapidly as migration into cities continue. The density of cities provides residents access to places, people, and goods, but also gives rise to problems related to health, congestion, and safety. In parallel to rapid urbanization, ubiquitous mobile computing, namely the pervasive use of cellular phones, has generated a wealth of data that can be analyzed to understand and improve urban systems. These devices and the applications that run on them passively record social, mobility, and a variety of other behaviors of their users with extremely high spatial and temporal resolution. This thesis presents a variety of novel methods and analyses to leverage the data generated from these devices to understand human behavior within cities. It details new ways to measure and quantify human behaviors related to mobility, social influence, and economic outcomes.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Jameson Lawrence Toole.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">Ph.D.</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">241 pages</dim:field>
   <dim:field mdschema="dc" element="language" qualifier="iso" lang="en_US">eng</dim:field>
   <dim:field mdschema="dc" element="publisher" lang="en_US">Massachusetts Institute of Technology</dim:field>
   <dim:field mdschema="dc" element="rights" lang="en_US">M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.</dim:field>
   <dim:field mdschema="dc" element="rights" qualifier="uri" lang="en_US">http://dspace.mit.edu/handle/1721.1/7582</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">Engineering Systems Division.</dim:field>
   <dim:field mdschema="dc" element="title" lang="en_US">Putting big data in its place : understanding cities and human mobility with new data sources</dim:field>
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   	&lt;Title>Putting big data in its place : understanding cities and human mobility with new data sources&lt;/Title>
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   	&lt;PublicationDate>2015&lt;/PublicationDate>
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   	&lt;Abstract>According the United Nations Population Fund (UNFPA), 2008 marked the first year in which the majority of the planet&amp;apos;s population lived in cities. Urbanization, already over 80% in many western regions, is increasing rapidly as migration into cities continue. The density of cities provides residents access to places, people, and goods, but also gives rise to problems related to health, congestion, and safety. In parallel to rapid urbanization, ubiquitous mobile computing, namely the pervasive use of cellular phones, has generated a wealth of data that can be analyzed to understand and improve urban systems. These devices and the applications that run on them passively record social, mobility, and a variety of other behaviors of their users with extremely high spatial and temporal resolution. This thesis presents a variety of novel methods and analyses to leverage the data generated from these devices to understand human behavior within cities. It details new ways to measure and quantify human behaviors related to mobility, social influence, and economic outcomes.&lt;/Abstract>
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