A cognitive categorization-based approach for understanding identity representation online
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.
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| Other Authors: | |
| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2013
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| Online Access: | http://hdl.handle.net/1721.1/76994 |
| _version_ | 1811081568725237760 |
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| author | Vargas, Gregory G |
| author2 | Fox Harrell. |
| author_facet | Fox Harrell. Vargas, Gregory G |
| author_sort | Vargas, Gregory G |
| collection | MIT |
| description | Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. |
| first_indexed | 2024-09-23T11:48:42Z |
| format | Thesis |
| id | mit-1721.1/76994 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:48:42Z |
| publishDate | 2013 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/769942019-04-12T21:36:10Z A cognitive categorization-based approach for understanding identity representation online Cognitive categorization-based approach to assist in understanding identity representations in social networks Vargas, Gregory G Fox Harrell. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011. Cataloged from PDF version of thesis. Includes bibliographical references (p. 99-100). Computationally representing social identities using social networking profiles traditionally involves the reduction of identities to fit into simplistic categories such as "friends." In contrast, this thesis proposes that the data structures underlying user identities can be algorithmically processed and interpreted in ways that assist in understanding more nuanced aspects of identity such as "subculture" or"personality" Building upon an interdisciplinary computational identity model developed by Fox Harrell in his NSF-supported Advanced Identity Representation Project, this thesis proposes an algorithm based on theories of cognitive categorization[6, 7] to reveal implicit categories in computational identity systems. The algorithm has been applied to social networking site Facebook and a suite of graphical user interfaces was developed to enable users to explore individual and group identities. In a qualitative study, we found that most of the generated categories coherently represented social groups and would be useful for applications such as expressing the groups' collective identities. by Gregory G. Vargas. M.Eng. 2013-02-14T15:36:13Z 2013-02-14T15:36:13Z 2011 2011 Thesis http://hdl.handle.net/1721.1/76994 825555258 eng 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. http://dspace.mit.edu/handle/1721.1/7582 100 p. application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Vargas, Gregory G A cognitive categorization-based approach for understanding identity representation online |
| title | A cognitive categorization-based approach for understanding identity representation online |
| title_full | A cognitive categorization-based approach for understanding identity representation online |
| title_fullStr | A cognitive categorization-based approach for understanding identity representation online |
| title_full_unstemmed | A cognitive categorization-based approach for understanding identity representation online |
| title_short | A cognitive categorization-based approach for understanding identity representation online |
| title_sort | cognitive categorization based approach for understanding identity representation online |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/76994 |
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