<?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>2026-09-19T02:25:19Z</responseDate><request verb="GetRecord" identifier="oai:dspace.mit.edu:1721.1/106237" metadataPrefix="dim">https://dspace.mit.edu/server/oai/request</request><GetRecord><record><header><identifier>oai:dspace.mit.edu:1721.1/106237</identifier><datestamp>2022-01-13T07:55:19Z</datestamp><setSpec>com_1721.1_7582</setSpec><setSpec>com_1721.1_7581</setSpec><setSpec>col_1721.1_131023</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">Peter Gloor.</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="author" lang="en_US">Hamdouch, Ilias</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" lang="en_US">Massachusetts Institute of Technology. Engineering and Management Program</dim:field>
   <dim:field mdschema="dc" element="contributor" qualifier="department" lang="en_US">System Design and Management Program.</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="accessioned">2017-01-06T16:13:17Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="available">2017-01-06T16:13:17Z</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="copyright" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="date" qualifier="issued" lang="en_US">2015</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="uri">http://hdl.handle.net/1721.1/106237</dim:field>
   <dim:field mdschema="dc" element="identifier" qualifier="oclc" lang="en_US">961358167</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Thesis: S.M. in Engineering and Management, Massachusetts Institute of Technology, School of Engineering, System Design and Management Program, Engineering and Management Program, 2015.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Cataloged from PDF version of thesis.</dim:field>
   <dim:field mdschema="dc" element="description" lang="en_US">Includes bibliographical references (pages 66-68).</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="abstract" lang="en_US">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.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="statementofresponsibility" lang="en_US">by Ilias Hamdouch.</dim:field>
   <dim:field mdschema="dc" element="description" qualifier="degree" lang="en_US">S.M. in Engineering and Management</dim:field>
   <dim:field mdschema="dc" element="format" qualifier="extent" lang="en_US">80 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 and Management Program.</dim:field>
   <dim:field mdschema="dc" element="subject" lang="en_US">System Design and Management Program.</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">Collective intelligence at Enron during the California energy crisis : uncovering collaborative innovation networks using social network analysis</dim:field>
   <dim:field mdschema="dc" element="title" qualifier="alternative" lang="en_US">Uncovering collaborative innovation networks using social network analysis</dim:field>
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   	&lt;Title>Collective intelligence at Enron during the California energy crisis : uncovering collaborative innovation networks using social network analysis&lt;/Title>
   	&lt;Subtitle>Uncovering collaborative innovation networks using social network analysis&lt;/Subtitle>
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   	&lt;PublicationDate>2015&lt;/PublicationDate>
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   	&lt;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&amp;apos;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.&lt;/Abstract>
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