Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy
Social networks have been used to understand how information flows through an organization as well as identifying individuals that appear to have control over this information flow. Such individuals are identified as being central nodes in a graph representation of the social network and have high...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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2005
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| Online Access: | http://hdl.handle.net/1721.1/30288 |
| _version_ | 1826216047990013952 |
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| author | Rudolph, Larry Zhenghao, Chen |
| author_facet | Rudolph, Larry Zhenghao, Chen |
| author_sort | Rudolph, Larry |
| collection | MIT |
| description | Social networks have been used to understand how information flows through an organization as well as identifying individuals that appear to have control over this information flow. Such individuals are identified as being central nodes in a graph representation of the social network and have high "betweenness" values. Rather than looking at graphs derived from email, on-line forums, or telephone connections, we consider sequences of bipartite graphs that represent face-to-face meetings between individuals, and define a new metric to identify the information elite individuals. We show that, in our simulations, individuals that attend many meetings with many different people do not always have high betweenness values, even though they seem to be the ones that control the information flow. |
| first_indexed | 2024-09-23T16:41:28Z |
| format | Article |
| id | mit-1721.1/30288 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T16:41:28Z |
| publishDate | 2005 |
| record_format | dspace |
| spelling | mit-1721.1/302882019-04-11T07:03:43Z Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy Rudolph, Larry Zhenghao, Chen social networks universal hashing privacy information flow pervasive computing face-to-face meetings models location tracking Social networks have been used to understand how information flows through an organization as well as identifying individuals that appear to have control over this information flow. Such individuals are identified as being central nodes in a graph representation of the social network and have high "betweenness" values. Rather than looking at graphs derived from email, on-line forums, or telephone connections, we consider sequences of bipartite graphs that represent face-to-face meetings between individuals, and define a new metric to identify the information elite individuals. We show that, in our simulations, individuals that attend many meetings with many different people do not always have high betweenness values, even though they seem to be the ones that control the information flow. Singapore-MIT Alliance (SMA) 2005-12-14T19:42:37Z 2005-12-14T19:42:37Z 2006-01 Article http://hdl.handle.net/1721.1/30288 en Computer Science (CS) 2219317 bytes application/pdf application/pdf |
| spellingShingle | social networks universal hashing privacy information flow pervasive computing face-to-face meetings models location tracking Rudolph, Larry Zhenghao, Chen Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy |
| title | Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy |
| title_full | Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy |
| title_fullStr | Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy |
| title_full_unstemmed | Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy |
| title_short | Modeling Information Flow in Face-to-Face Meetings while Protecting Privacy |
| title_sort | modeling information flow in face to face meetings while protecting privacy |
| topic | social networks universal hashing privacy information flow pervasive computing face-to-face meetings models location tracking |
| url | http://hdl.handle.net/1721.1/30288 |
| work_keys_str_mv | AT rudolphlarry modelinginformationflowinfacetofacemeetingswhileprotectingprivacy AT zhenghaochen modelinginformationflowinfacetofacemeetingswhileprotectingprivacy |