{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/106237"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/106237","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Collective intelligence at Enron during the California energy crisis : uncovering collaborative innovation networks using social network analysis","abstract":"As interaction takes place between individuals, relationships are formed and collaboration and innovation emerge. In this thesis I have applied Coolfarming (Gloor, 201 lb), a social network analysis method using Condor, a software tool to quantify communication patterns based on various data sources. I analyzed the Enron email archive to see if communication patterns of convicted employees differ from ordinary ones. Toward that goal, I compared the dynamic semantic social network metrics of 17 Enron employees convicted in the criminal trial following Enron's implosion with a control group of ordinary employees. I focused on 17 mailboxes of 24 Enron executives that were convicted. Identifying criminals based on email behaviors is possible depending on the sampling strategy. When sampling based on employees with comparable total emails, the statistical analysis of the Contribution Index (Ci) metric revealed that criminals were less active. When sampling based on employees with comparable total influence, the statistical analysis of Betweenness Centrality Oscillation (Bco) and Degree Centrality (Bc) metrics revealed that criminals were less connected to others and less creative.","abstract_html":"As interaction takes place between individuals, relationships are formed and collaboration and innovation emerge. In this thesis I have applied Coolfarming (Gloor, 201 lb), a social network analysis method using Condor, a software tool to quantify communication patterns based on various data sources. I analyzed the Enron email archive to see if communication patterns of convicted employees differ from ordinary ones. Toward that goal, I compared the dynamic semantic social network metrics of 17 Enron employees convicted in the criminal trial following Enron's implosion with a control group of ordinary employees. I focused on 17 mailboxes of 24 Enron executives that were convicted. Identifying criminals based on email behaviors is possible depending on the sampling strategy. When sampling based on employees with comparable total emails, the statistical analysis of the Contribution Index (Ci) metric revealed that criminals were less active. When sampling based on employees with comparable total influence, the statistical analysis of Betweenness Centrality Oscillation (Bco) and Degree Centrality (Bc) metrics revealed that criminals were less connected to others and less creative.","abstract_has_math":false,"creators":["Hamdouch, Ilias"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Engineering and Management Program","school":null,"contributors":[],"advisors":["Peter Gloor."],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-22T22:21:25Z","subjects":["Engineering and Management Program.","System Design and Management Program.","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/1721.1/106237","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Peter Gloor."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Engineering and Management Program","System Design and Management Program.","Massachusetts Institute of Technology. Engineering Systems Division.","System Design and Management Program"]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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In this thesis I have applied Coolfarming (Gloor, 201 lb), a social network analysis method using Condor, a software tool to quantify communication patterns based on various data sources. I analyzed the Enron email archive to see if communication patterns of convicted employees differ from ordinary ones. Toward that goal, I compared the dynamic semantic social network metrics of 17 Enron employees convicted in the criminal trial following Enron's implosion with a control group of ordinary employees. I focused on 17 mailboxes of 24 Enron executives that were convicted. Identifying criminals based on email behaviors is possible depending on the sampling strategy. When sampling based on employees with comparable total emails, the statistical analysis of the Contribution Index (Ci) metric revealed that criminals were less active. When sampling based on employees with comparable total influence, the statistical analysis of Betweenness Centrality Oscillation (Bco) and Degree Centrality (Bc) metrics revealed that criminals were less connected to others and less creative."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M. in Engineering and Management"]},{"key":"dc:title","label":"Title","values":["Collective intelligence at Enron during the California energy crisis : uncovering collaborative innovation networks using social network analysis"]}]}],"canonical_facts":{"dc:contributor.advisor":["Peter Gloor."],"dc:contributor.department":["Massachusetts Institute of Technology. Engineering and Management Program","System Design and Management Program.","Massachusetts Institute of Technology. Engineering Systems Division.","System Design and Management Program"],"dc:contributor.other":["Massachusetts Institute of Technology. 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Toward that goal, I compared the dynamic semantic social network metrics of 17 Enron employees convicted in the criminal trial following Enron's implosion with a control group of ordinary employees. I focused on 17 mailboxes of 24 Enron executives that were convicted. Identifying criminals based on email behaviors is possible depending on the sampling strategy. When sampling based on employees with comparable total emails, the statistical analysis of the Contribution Index (Ci) metric revealed that criminals were less active. 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