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Looking for Resource to Understand UCINET Centrality Measures
Hello Everyone,?
I am a PhD student using social network analysis for part of my dissertation. I am trying to understand all of the options for generating centrality measures in UCINET. Is there a resource which defines each of the options presented? I have found descriptions of many of them online but I cannot find anything for 2-step Betweenness for example. I do have the Analyzing Social Networks book.? My Analysis so far: My data is a binary (0 and 1) symmetric matrix witch is directed (Who did you borrow from). I want to compare measures across networks (I have 12 total - 6 for borrowing and 6 for who you lent to) so I have selected to report normalized scores. I don't know what Beta, K, or Frag meth are so I left those at their default. For now I selected to generate all measures which gave me results for Step Between, Between, InClose, OutClose, In2Local, Out2Local, InDegree, OutDegree, Out Eigen, and In Eigen.? Below is the screen I am trying to understand.? Thank you in advance.? Best,? Leslie |
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You can look up the operational definition of most the measures in the Ucinet Help menu, and it many cases useful references to classic articles are provided.
Some of these are also described in the free open-access textbook by Hanneman and Riddle:
DBT
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From: [email protected] <[email protected]> on behalf of lbf5170@... <lbf5170@...>
Sent: March 11, 2024 6:17 AM To: [email protected] Subject: [ucinet] Looking for Resource to Understand UCINET Centrality Measures ?
I am a PhD student using social network analysis for part of my dissertation. I am trying to understand all of the options for generating centrality measures in UCINET. Is there a resource which defines each of the options presented? I have found descriptions of many of them online but I cannot find anything for 2-step Betweenness for example. I do have the Analyzing Social Networks book.? My Analysis so far: My data is a binary (0 and 1) symmetric matrix witch is directed (Who did you borrow from). I want to compare measures across networks (I have 12 total - 6 for borrowing and 6 for who you lent to) so I have selected to report normalized scores. I don't know what Beta, K, or Frag meth are so I left those at their default. For now I selected to generate all measures which gave me results for Step Between, Between, InClose, OutClose, In2Local, Out2Local, InDegree, OutDegree, Out Eigen, and In Eigen.? Below is the screen I am trying to understand.? Thank you in advance.? Best,? Leslie |
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¿ªÔÆÌåÓýLeslie, imagine that betweenness is (loosely) the number of shortest paths between everyone and everyone that pass through a given node, k, weighted inversely by the number of equally short paths between the same pairs. For example, suppose we have the following ties: i -> k, k -> j, i -> p, ?p -> j, and j -> q. ? ? Then, with normal betweenness, node k will receive a half a point for being along one of the two equally short paths from i to j as well as another half point for being along one of the two shortest paths from i to q. But in 2-step betweenness, k will only receive points for paths of length two. So the path from i to q won¡¯t count, as it is of length of 3. ? The reason for using 2-step betweenness is that for some kinds of social processes, such as brokering, we feel that only direct connections matter. So node k brokers the relationship between its two direct contacts i and j, but may not even be aware of q.? 2-step betweenness is particularly useful as an alternative to Burt¡¯s structural hole measures because they take into account nodes that are not in an ego¡¯s network. For example, k¡¯s network consists only of i and j, not p. Structural hole measures will think that k is in a great position. But they don¡¯t take into account the existence of p, who is also brokering between the exact same two people, and diluting k¡¯s position. ? steve ? ? ? ? Stephen P. Borgatti Carol Martin Gatton Chair of Management Gatton College of Business and Economics University of Kentucky ? From: [email protected] <[email protected]>
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Sent: Monday, March 11, 2024 09:18 To: [email protected] Subject: [ucinet] Looking for Resource to Understand UCINET Centrality Measures ?
CAUTION: External Sender ? Hello Everyone,? |