{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/98631"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/98631","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Putting big data in its place : understanding cities and human mobility with new data sources","abstract":"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.","abstract_html":"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.","abstract_has_math":false,"creators":["Toole, Jameson Lawrence"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Engineering Systems Division.","school":null,"contributors":[],"advisors":["Marta C. Gonzàlez, Joseph M. Sussman and P. Christopher Zegras."],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-22T22:21:35Z","subjects":["Engineering Systems Division."],"languages":["eng"],"rights":["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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/98631","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Marta C. Gonzàlez, Joseph M. Sussman and P. 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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."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. D."]},{"key":"dc:title","label":"Title","values":["Putting big data in its place : understanding cities and human mobility with new data sources"]}]}],"canonical_facts":{"dc:contributor.advisor":["Marta C. Gonzàlez, Joseph M. Sussman and P. Christopher Zegras."],"dc:contributor.department":["Massachusetts Institute of Technology. Engineering Systems Division."],"dc:contributor.other":["Massachusetts Institute of Technology. Engineering Systems Division."],"dc:creator":["Toole, Jameson Lawrence"],"dc:date.accessioned":["2015-09-17T19:00:56Z"],"dc:date.available":["2015-09-17T19:00:56Z"],"dc:date.issued":["2015"],"dc:description":["Thesis: Ph. 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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."],"dc:description.degree":["Ph. D."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/98631"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["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."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Engineering Systems Division."],"dc:title":["Putting big data in its place : understanding cities and human mobility with new data sources"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:35Z"}