2026-09-19T02:39:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/765242022-01-13T07:55:03Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Andrew B. Lippman.
Ma, Julia Shuhong
Massachusetts Institute of Technology. Dept. of Architecture. Program in Media Arts and Sciences.
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
2013-01-23T19:48:41Z
2013-01-23T19:48:41Z
2012
2012
http://hdl.handle.net/1721.1/76524
823868124
Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2012.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 95-100).
This thesis applies network theory to firms, their employees, and various aspects of the employees to understand diversity within an industry at both the firm-level and employee-level. We hypothesize that the interest diversity of a firms' employee can influence that firm's economic performance and growth. Using the LinkedIn API, we are able to collect ~600 employees (past and present) for 43 companies using a keyword search. This data is used to create a visualization of people's interests, an "Interest Space", which is a network graph of how interests are categorized and linked to each other. By analyzing the data from firms associated with the Media Lab, we begin to understand how individual interests affect success among a small network of companies. We research this through case studies of a few companies by analyzing their financial data and interests of their employees.
by Julia Shuhong Ma.
S.M.
100 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Architecture. Program in Media Arts and Sciences.
Interest networks : understanding the influence of interesting people in an organization
Diversity networks : understanding the influence of interesting people in an organization
Thesis
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Publication
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<Abstract>This thesis applies network theory to firms, their employees, and various aspects of the employees to understand diversity within an industry at both the firm-level and employee-level. We hypothesize that the interest diversity of a firms' employee can influence that firm's economic performance and growth. Using the LinkedIn API, we are able to collect ~600 employees (past and present) for 43 companies using a keyword search. This data is used to create a visualization of people's interests, an "Interest Space", which is a network graph of how interests are categorized and linked to each other. By analyzing the data from firms associated with the Media Lab, we begin to understand how individual interests affect success among a small network of companies. We research this through case studies of a few companies by analyzing their financial data and interests of their employees.</Abstract>
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