[CollEc] CollEc App Offline

[Düben, Christian]

Sorry, I meant multiplying by (sum d)^2 / N, of course.

Christian Düben
Research Associate
Chair of Macroeconomics
Hamburg University
Von-Melle-Park 5, Room 3102
20146 Hamburg
Germany
+49 40 42838 1898
christian.dueben at uni-hamburg.de
http://www.christian-dueben.com

-----Original Message-----
From: CollEc-run <collec-run-bounces at lists.openlib.org> On Behalf Of Düben, Christian
Sent: Mittwoch, 30. Dezember 2020 10:46
To: Thomas Krichel <krichel at openlib.org>
Cc: CollEc Run <collec-run at lists.openlib.org>
Subject: Re: [CollEc] CollEc App Offline

I do use binary paths here. Weighted paths are not exported.

As far as I understand it, there is one fixed closeness formula: 1 / (sum d). Just like the definitions of the mean, the variance, and other statistical measures are fixed. Your alternative measure appears to be (sum d) / N. Thus, multiplying my results by d^2 / N should produce your results. This is not about different path defintions. The former CollEc's closeness values are simply a scaled version of the new CollEc's closeness values. How does this make my results counter-intuitive? There is nothing different about the underlying paths.

Christian Düben
Research Associate
Chair of Macroeconomics
Hamburg University
Von-Melle-Park 5, Room 3102
20146 Hamburg
Germany
+49 40 42838 1898
christian.dueben at uni-hamburg.de
http://www.christian-dueben.com

-----Original Message-----
From: Thomas Krichel <krichel at openlib.org>
Sent: Mittwoch, 30. Dezember 2020 04:27
To: Düben, Christian <Christian.Dueben at uni-hamburg.de>
Cc: CollEc Run <collec-run at lists.openlib.org>
Subject: Re: [CollEc] CollEc App Offline

  Düben, Christian writes

> Thomas, how do you get closeness values larger than 1?

  I use common sense. The closeness of a person is the
  average distance from one to any other, for all others.
  Since the distance between any pair is at least one,
  the average must be larger than one. 

> Do you scale the results by some factor?

  No.

> Or is the distance between co-authors not 1 in your case?

  It is.

> With the closeness equation of C(v) = 1 / (\sum_{i \neq v} d(v, i)) 
> where d(v, i) is the length of the shortest cost path between author v 
> and author i and d(v, i) \geq 1, any closeness value should be between
> 0 and 1.

  There is something counter-intuitive in this approach. 

  I said many times, if we don't use a binary model, we will leave our
  users confused. Alternative weighing schemes should be used to
  filter out from binary short paths that have the same
  length. However, the way you do that will not have any impact on the
  closeness, as expressed in my common sense understanding. It will
  only impact the betweenness.

-- 

  Cheers,

  Thomas Krichel                  http://openlib.org/home/krichel
                                              skype:thomaskrichel

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