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Re: 2-Local Eigenvector Centrality

 

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It’s the sum of degrees of one’s friends. For example, look at Jennie in this picture

?

Her friends are Pat, Pam and Ann. Pat has 4 friends, Pam has 5 and Ann has 3. The sum is 12, which is Jennie’s “2-local eigenvector” score.

?

steve

?

From: ucinet@...
Sent: Sunday, April 14, 2019 14:06
To: ucinet@...
Subject: [UCINET] 2-Local Eigenvector Centrality

?

?

I understand most centrality measures but can not find a definition of 2-local eigenvector centrality or a reference citation. Any suggestions? Thank you.


2-Local Eigenvector Centrality

 

I understand most centrality measures but can not find a definition of 2-local eigenvector centrality or a reference citation. Any suggestions? Thank you.


Network analysis postdoc at the University of Kentucky's LINKS Center

 

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The Gatton College of Business and Economics’ Department of Management invites applications for a one-year postdoctoral position in the area of social network analysis and network science, with a focus on scientific collaboration and team science.

This is a position involving research between the University of Kentucky’s (UK) LINKS Center for Social Network Analysis, the UK Center for Clinical and Translational Science (CCTS), and the University of Florida. The candidate will be an active participant in the LINKS Center, the preeminent center for the study of social networks in organizations, which is housed in the Department of Management. The LINKS Center hosts an annual workshop on network methods and analysis, a biennial small conference that attracts many of the top faculty in social network analysis from around the world, and an active seminar series. More information about the LINKS Center can be found at . The UK Center for Clinical and Translational Science () unites clinicians, researchers, and communities through innovative team science to accelerate the translation of basic science discoveries to tangible improvements in health.

The ideal candidate should have expertise in social network analysis, network science, and data science (including familiarity with R, Python and databases), and an interest in the study of science and scientific collaboration. Familiarity with Natural Language Processing will be considered a plus. The candidate should hold a Ph.D. in a related area, although exceptional Ph.D. candidates at the ABD stage might also be considered.

The position will open immediately and cover a one-year term; a renewal is possible pending funding renewal. To apply, interested applicants should apply online at: .

Applications must include the following: a cover letter detailing your expertise and research interests (upload under Specific Request 1), an academic transcript, and a curriculum vitae. You will be asked to provide the names and contact information for at least two references when prompted in the application (upload under Specific Request 2). This information will be utilized to solicit recommendation letters from your references within the employment system.? Applications will be received until the position is filled.

Over the last 95 years, UK’s Gatton College of Business and Economics has been preparing principled leaders for the global economy, producing high quality, influential research, and supporting economic growth in Kentucky and beyond. Accredited by the AACSB, Gatton proudly offers a full range of undergraduate, graduate and professional business and economics degrees and certificates. We are housed in a recently renovated 220,000 square foot state-of-the-art facility where the college accommodates the fastest growing enrollment on UK’s campus, expected to reach over 4,000 Students by fall of 2019. Through teaching, research, and outreach, the Gatton College has a direct, tangible influence on the lives of Kentucky’s citizens and people around the world. We are looking for professionals who embody the College’s tagline of “Blue Means Business”. Please consider joining our team.

The University of Kentucky is committed to a diverse and inclusive workforce by ensuring all our students, faculty, and staff work in an environment of openness and acceptance. We strive to foster a community where people of all backgrounds, identities, and perspectives can feel secure and welcome. We also value the well-being of each of our employees and are dedicated to creating a healthy place to work, learn and live. In the interest of maintaining a safe and healthy environment for our students, employees, patients and visitors the University of Kentucky is a Tobacco & Drug Free campus. As an Equal Opportunity Employer, we strongly encourage veterans, individuals with disabilities, women, and all minorities to consider our employment opportunities.

steve


Export to Pajek Net File

 

I'm having problems with exporting my data (116 symmetric) file to Pajek net format. I can easily do the task with Southern Women dataset or Knokburr, but UCINET crashes whenever it tries my dataset. Displaying the data shows it is a well structured file in UCINET. Any ideas wuld be welcome.


2-Local Eigenvector Centrality

 

When calculating centralities, 2-Local? (eigenvector centrality) is also computed. Where might one find a explanation or comparison with eigenvector centrality? Not found so far in the Help or searches online. Thanks.


UCINET-oriented Introductory workshop on social network analysis

 

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Please join Statistical Horizons in Philadelphia for a 2-day seminar...

Introduction to Social Network Analysis
Taught by Dr. Stephen Borgatti
May 3-4, 2019, Philadelphia

This 2-day intensive workshop provides an introduction to doing research on social networks. The course is very hands-on, emphasizing mastering the software and using the concepts and methods to answer research questions. We will use the UCINET software package.

Register before April 3 to receive early registration pricing.

?

?

Contact us at?info@....?

?

?

Stephen P. Borgatti

Paul Chellgren Endowed Chair and Professor

Dept. of Management

Gatton College of Business and Economics

University of Kentucky

steve.borgatti@...

?


2019 Summer SNA/UCINET Workshops

 

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Of potential interest to the list:

I am teaching two workshops this summer on Social Network Analysis using UCINET. ?

They are:

May 28-31
A 3.5 Day workshop the week after Memorial Day
Hosted by Fresno State University in Central California
In the shadow of Yosemite National Park
Includes a keynote address by Steve Borgatti
http://www.fresnostate.edu/craig/depts-programs/mgt/snaworkshop/


June 6-8
A 2.5 Day "short course" through CARMA
The Consortium for the Advancement of Research Methods & Analysis
Hosted at Wayne State University in Detroit, MI
Make a week of it with an additional short course available June 3-5
https://business.unl.edu/outreach/carma/short-courses/



Rich DeJordy, Ph.D.
dejordy@...
Assistant Professor
SubDirect Research Fellow
Management Department
Craig School of Business
California State University, Fresno



Re: Problem generating centrality scores

 

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Jordan, can you send me the data (steve.borgatti@...)?

?

steve

?

From: ucinet@...
Sent: Saturday, March 30, 2019 15:17
To: Jordan Tchilingirian
Subject: [UCINET] Problem generating centrality scores

?

?

Dear group,

?

Sorry to disturb your weekend.

?

I’m having a spot of bother with centrality scores and was wondering if anyone has a solution or work around.

?

Data: Valued 1 mode (4028 x 4028) created from a 2 mode network (4028 x 100).

?

Problem: I am unable to generate centrality scores for 1 mode networks - this includes the multiple measures function, single measures, and the legacy Degree centrality option. ?UCInet either times out or simply doesn’t produce the scores

?

The 2 mode centrality function works fine and there are no issues with other functions for 1 mode networks (e.g. cohesion). I have worked with similar sized networks in the past and have never had this issue. UCinet is up to date

?

Any help would be greatly appreciated.

?

Best wishes,

?

Jordan

?

Dr. Jordan Soukias Tchilingirian
Lecturer
Department of Social and Policy Sciences
University of Bath
Office: 3 East 4.14
Phone: +44(0)125 386861

?


Problem generating centrality scores

 

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Dear group,

?

Sorry to disturb your weekend.

?

I’m having a spot of bother with centrality scores and was wondering if anyone has a solution or work around.

?

Data: Valued 1 mode (4028 x 4028) created from a 2 mode network (4028 x 100).

?

Problem: I am unable to generate centrality scores for 1 mode networks - this includes the multiple measures function, single measures, and the legacy Degree centrality option. ?UCInet either times out or simply doesn’t produce the scores

?

The 2 mode centrality function works fine and there are no issues with other functions for 1 mode networks (e.g. cohesion). I have worked with similar sized networks in the past and have never had this issue. UCinet is up to date

?

Any help would be greatly appreciated.

?

Best wishes,

?

Jordan

?

Dr. Jordan Soukias Tchilingirian
Lecturer
Department of Social and Policy Sciences
University of Bath
Office: 3 East 4.14
Phone: +44(0)125 386861

?


Re: interpretation of t-test results

 

Thank you so much for the reply, helps a lot!


---In ucinet@..., <steve.borgatti@...> wrote :

It might be clearer to say that, across 10,000 random assignments of persons to groups, the probability of observing a difference as large as 29.756 is exceedingly low – less than .001. But yes, group 2 members have many more ties (or higher strengths of tie), on average, than do members of group 1. Of course, group 2 seems like a very select group, just 31 members against 769 in the other group.

?

?

From: ucinet@... <ucinet@...>
Sent: Thursday, March 28, 2019 17:27
To: ucinet@...
Subject: [UCINET] interpretation of t-test results

?

?

Hi! it's the first time I use the t-test tool and I just want to make sure I interpreted the results correctly.

I am posting the results of the Tools>Testing Hypotheses>Node-Level>T-Test

my dependent is degree centrality, my independent is a dummy variable indicating if an actor possess a specific attribute and thus belongs to group 1 or 2. My hypothesis is that actors in group 2 are more central (degree centrality). My understanding is that the av degree centrality of group 1 is 29.756 units lower than the av degree of group 2, and that differences up to -29.756 happen in favour of group 1 100% of the time in random trials. Could we argue that actors in group 2 tend to have an higher degree centrality? would that be correct?

?

?

_______

Basic statistics on each group.

?????????????????????????? 1????????? 2
???????????????????? Group 1??? Group 2
????????????????? ---------- ----------
??? 1?????? Mean?????? 5.857???? 35.613
??? 2??? Std Dev????? 15.708???? 39.457
??? 3??????? Sum??? 4504.000?? 1104.000
??? 4?? Variance???? 246.726?? 1556.882
??? 5??????? SSQ? 216112.000? 87580.000
??? 6????? MCSSQ? 189732.266? 48263.355
??? 7?? Euc Norm???? 464.878??? 295.939
??? 8??? Minimum?????? 0.000????? 1.000
??? 9??? Maximum???? 337.000??? 148.000
?? 10?? N of Obs???? 769.000???? 31.000
?? 11? N Missing????? 31.000??? 769.000


SIGNIFICANCE TESTS

???? Difference??????? ...One-Tailed Tests...???? Two-Tailed
?????? in Means??? Group 1 > 2??? Group 2 > 1?????????? Test
?============== ============== ============== ==============
??????? -29.756????????? 1.000????????? 0.000???????? 0.0001

?

?


Re: interpretation of t-test results

 

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It might be clearer to say that, across 10,000 random assignments of persons to groups, the probability of observing a difference as large as 29.756 is exceedingly low – less than .001. But yes, group 2 members have many more ties (or higher strengths of tie), on average, than do members of group 1. Of course, group 2 seems like a very select group, just 31 members against 769 in the other group.

?

?

From: ucinet@...
Sent: Thursday, March 28, 2019 17:27
To: ucinet@...
Subject: [UCINET] interpretation of t-test results

?

?

Hi! it's the first time I use the t-test tool and I just want to make sure I interpreted the results correctly.

I am posting the results of the Tools>Testing Hypotheses>Node-Level>T-Test

my dependent is degree centrality, my independent is a dummy variable indicating if an actor possess a specific attribute and thus belongs to group 1 or 2. My hypothesis is that actors in group 2 are more central (degree centrality). My understanding is that the av degree centrality of group 1 is 29.756 units lower than the av degree of group 2, and that differences up to -29.756 happen in favour of group 1 100% of the time in random trials. Could we argue that actors in group 2 tend to have an higher degree centrality? would that be correct?

?

?

_______

Basic statistics on each group.

?????????????????????????? 1????????? 2
???????????????????? Group 1??? Group 2
????????????????? ---------- ----------
??? 1?????? Mean?????? 5.857???? 35.613
??? 2??? Std Dev????? 15.708???? 39.457
??? 3??????? Sum??? 4504.000?? 1104.000
??? 4?? Variance???? 246.726?? 1556.882
??? 5??????? SSQ? 216112.000? 87580.000
??? 6????? MCSSQ? 189732.266? 48263.355
??? 7?? Euc Norm???? 464.878??? 295.939
??? 8??? Minimum?????? 0.000????? 1.000
??? 9??? Maximum???? 337.000??? 148.000
?? 10?? N of Obs???? 769.000???? 31.000
?? 11? N Missing????? 31.000??? 769.000


SIGNIFICANCE TESTS

???? Difference??????? ...One-Tailed Tests...???? Two-Tailed
?????? in Means??? Group 1 > 2??? Group 2 > 1?????????? Test
?============== ============== ============== ==============
??????? -29.756????????? 1.000????????? 0.000???????? 0.0001

?

?


interpretation of t-test results

 

Hi! it's the first time I use the t-test tool and I just want to make sure I interpreted the results correctly.
I am posting the results of the Tools>Testing Hypotheses>Node-Level>T-Test
my dependent is degree centrality, my independent is a dummy variable indicating if an actor possess a specific attribute and thus belongs to group 1 or 2. My hypothesis is that actors in group 2 are more central (degree centrality). My understanding is that the av degree centrality of group 1 is 29.756 units lower than the av degree of group 2, and that differences up to -29.756 happen in favour of group 1 100% of the time in random trials. Could we argue that actors in group 2 tend to have an higher degree centrality? would that be correct?


_______
Basic statistics on each group.

?????????????????????????? 1????????? 2
???????????????????? Group 1??? Group 2
????????????????? ---------- ----------
??? 1?????? Mean?????? 5.857???? 35.613
??? 2??? Std Dev????? 15.708???? 39.457
??? 3??????? Sum??? 4504.000?? 1104.000
??? 4?? Variance???? 246.726?? 1556.882
??? 5??????? SSQ? 216112.000? 87580.000
??? 6????? MCSSQ? 189732.266? 48263.355
??? 7?? Euc Norm???? 464.878??? 295.939
??? 8??? Minimum?????? 0.000????? 1.000
??? 9??? Maximum???? 337.000??? 148.000
?? 10?? N of Obs???? 769.000???? 31.000
?? 11? N Missing????? 31.000??? 769.000


SIGNIFICANCE TESTS

???? Difference??????? ...One-Tailed Tests...???? Two-Tailed
?????? in Means??? Group 1 > 2??? Group 2 > 1?????????? Test
?============== ============== ============== ==============
??????? -29.756????????? 1.000????????? 0.000???????? 0.0001

?



Re: confused with the answer from the calculation of UCINET [1 Attachment]

 

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Jen, try

?

->dsp centdiff(padgm padgb undir)

?

As for densitydiff, as I explained before, your version of the program is calculating things correctly but is printing the wrong label: in the output, it is using the word centralization instead of density. This has been corrected, but you would have to download the current version to see it.

?

steve

?

From: ucinet@... <ucinet@...>
Sent: Thursday, March 21, 2019 08:12
To: 'Steve Borgatti' steve.borgatti@... [ucinet] <ucinet@...>
Subject: Re: [UCINET] confused with the answer from the calculation of UCINET [1 Attachment]

?

?

Dear Professor Borgatti:

Thank you for your information about my question!

I try to follow the steps you suggest. However, it always come up with the problems.?

Can you help me to solve the problem again?

For example, I try to compare the centralization of two different networks (logis 1 and logis 2). The analysis result come up with as follows which does not show any number to tell the analysis of difference. Is there any process wrong?

In addition, when I try to compare the density of two different networks, the software keeps showing me the wrong process message. I just don't understand what the problem is. Can you help me again!??

Thanks a lot!

?

?

任庆宗 感恩合十

=======================================
Ching Tsung Jen, Ph. D.
Adjunct?Associate Professor,?

Department of Logistics Management,?

National Defense University
M Phone: 0922435318
e-mail: malanyjen@...

=======================================
心不随境,是禪定的工夫

?

?

2019320 星期叁 上午10:15:16 [GMT+8] 'Steve Borgatti' steve.borgatti@... [ucinet]<ucinet@...> 写道:

?

?

?

Jen, first, you’re right: it’s mislabeled. But it is doing density. As for the numbers, is it possible your data are valued? If so, the program will use average tie strength. If your hand-calculating was based on dichotomized data, you would get different answers. You could do

?

->d1 = dichot(network1rows)

->d2 = dichot(network2rows)

->dsp densitydiff(d1 d2 undir)

?

steve

?

From: ucinet@... <ucinet@...>
Sent: Wednesday, March 6, 2019 21:32
To: ucinet@...
Subject: [UCINET] confused with the answer from the calculation of UCINET

?

?

Dear All:

I try to compare with the densities of two different networks. The result come as followings:

?

->dsp densitydiff(Network1Rows Netork2Rows undir)

?

Bootstrap SE1 = 0.1354

Bootstrap SE2 = 0.2363

T-statistic? ?= 1.3690

Cohen's d? ? ?= 1.9163

?

Test for equal degree centralization. 20000 iterations. Data are undirected.

?

? ? ? ? ? ? ? ? ? ?1?

? ? ? ? ? ? ? ?Measure?

? ? ? ? ? ? ? ?-----?

? ? 1? ?Network1 ROWS 0.506?

? ? 2? ?Network2 ROWS 0.875?

? ? 3 Obs Diff 0.369?

? ? 4? p-value 0..090?

4 rows, 1 columns, 1 levels.

?

?

I have two questions about the result.

First, the title of the result "Test for equal degree centralization.20000 iterations. Data are undirected." makes me a little confuse because I am testing the difference of density not the centralization. Why the title shows the test for equal degree centralization?

Secondly, it looks like that there is no significant difference between the two networks in terms of density.

My problem is the number of density calculated by UCINET is different from the number by hand calculation.

According to the result, the density of the? Network2 is 0.875. However, my hand calculation is only 0.0708. I don't understand what the problem come from. Can any one help me solve this confused problem.? Thanks a lot!

? ? ? ? ? ? ? ? ? ? ? Jen


Re: confused with the answer from the calculation of UCINET

 

Dear Professor Borgatti:
Thank you for your information about my question!
I try to follow the steps you suggest. However, it always come up with the problems.?
Can you help me to solve the problem again?
For example, I try to compare the centralization of two different networks (logis 1 and logis 2). The analysis result come up with as follows which does not show any number to tell the analysis of difference. Is there any process wrong?
In addition, when I try to compare the density of two different networks, the software keeps showing me the wrong process message. I just don't understand what the problem is. Can you help me again!??
Thanks a lot!




任庆宗 感恩合十
=======================================
Ching Tsung Jen, Ph. D.
Adjunct?Associate Professor,?
Department of Logistics Management,?
National Defense University
M Phone: 0922435318
e-mail: malanyjen@...

=======================================
心不随境,是禪定的工夫


在 2019年3月20日 星期叁 上午10:15:16 [GMT+8], 'Steve Borgatti' steve.borgatti@... [ucinet] 写道:


?

Jen, first, you’re right: it’s mislabeled. But it is doing density. As for the numbers, is it possible your data are valued? If so, the program will use average tie strength. If your hand-calculating was based on dichotomized data, you would get different answers. You could do

?

->d1 = dichot(network1rows)

->d2 = dichot(network2rows)

->dsp densitydiff(d1 d2 undir)

?

steve

?

From: ucinet@...
Sent: Wednesday, March 6, 2019 21:32
To: ucinet@...
Subject: [UCINET] confused with the answer from the calculation of UCINET

?

?

Dear All:

I try to compare with the densities of two different networks. The result come as followings:

?

->dsp densitydiff(Network1Rows Netork2Rows undir)

?

Bootstrap SE1 = 0.1354

Bootstrap SE2 = 0.2363

T-statistic? ?= 1.3690

Cohen's d? ? ?= 1.9163

?

Test for equal degree centralization. 20000 iterations. Data are undirected.

?

? ? ? ? ? ? ? ? ? ?1?

? ? ? ? ? ? ? ?Measure?

? ? ? ? ? ? ? ?-----?

? ? 1? ?Network1 ROWS 0.506?

? ? 2? ?Network2 ROWS 0.875?

? ? 3 Obs Diff 0.369?

? ? 4? p-value 0.090?

4 rows, 1 columns, 1 levels.

?

?

I have two questions about the result.

First, the title of the result "Test for equal degree centralization.20000 iterations. Data are undirected." makes me a little confuse because I am testing the difference of density not the centralization. Why the title shows the test for equal degree centralization?

Secondly, it looks like that there is no significant difference between the two networks in terms of density.

My problem is the number of density calculated by UCINET is different from the number by hand calculation.

According to the result, the density of the? Network2 is 0.875. However, my hand calculation is only 0.0708. I don't understand what the problem come from. Can any one help me solve this confused problem.? Thanks a lot!

? ? ? ? ? ? ? ? ? ? ? Jen


Re: confused with the answer from the calculation of UCINET

 

开云体育

Jen, first, you’re right: it’s mislabeled. But it is doing density. As for the numbers, is it possible your data are valued? If so, the program will use average tie strength. If your hand-calculating was based on dichotomized data, you would get different answers. You could do

?

->d1 = dichot(network1rows)

->d2 = dichot(network2rows)

->dsp densitydiff(d1 d2 undir)

?

steve

?

From: ucinet@...
Sent: Wednesday, March 6, 2019 21:32
To: ucinet@...
Subject: [UCINET] confused with the answer from the calculation of UCINET

?

?

Dear All:

I try to compare with the densities of two different networks. The result come as followings:

?

->dsp densitydiff(Network1Rows Netork2Rows undir)

?

Bootstrap SE1 = 0.1354

Bootstrap SE2 = 0.2363

T-statistic? ?= 1.3690

Cohen's d? ? ?= 1.9163

?

Test for equal degree centralization. 20000 iterations. Data are undirected.

?

? ? ? ? ? ? ? ? ? ?1?

? ? ? ? ? ? ? ?Measure?

? ? ? ? ? ? ? ?-----?

? ? 1? ?Network1 ROWS 0.506?

? ? 2? ?Network2 ROWS 0.875?

? ? 3 Obs Diff 0.369?

? ? 4? p-value 0.090?

4 rows, 1 columns, 1 levels.

?

?

I have two questions about the result.

First, the title of the result "Test for equal degree centralization.20000 iterations. Data are undirected." makes me a little confuse because I am testing the difference of density not the centralization. Why the title shows the test for equal degree centralization?

Secondly, it looks like that there is no significant difference between the two networks in terms of density.

My problem is the number of density calculated by UCINET is different from the number by hand calculation.

According to the result, the density of the? Network2 is 0.875. However, my hand calculation is only 0.0708. I don't understand what the problem come from. Can any one help me solve this confused problem.? Thanks a lot!

? ? ? ? ? ? ? ? ? ? ? Jen


Negative eigenvector values

 

Dear UCINET user group,


I used UCINET to calculate some network centrality measures, one of them is eigenvector measure, and I got many negative values of eigenvector although I have tried to check the box "Force majority of scores to be positive".


Is it correct to replace all negative values with zero?


I really appreciate if someone can help.


Thank you so much.


converting ucinet files to DL

 

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Dear UCInet user group,

?

Although I use netdraw regularly, I’m looking at some alternate data vis packages that are compatible with UCINet.


They often want DL files.

Looking at the UCInet help I have followed the below, after which the program (UCINET 6) crashes every time – even with small networks.

?

Procedure undertaken:

UCINET>Data>Export>DL (Screen shot follows)

?

As soon as press ok the system crashes L

Just wondering if others have had this issues, is there a work around, or is it ….user error? ;)

?

Thank you for your consideration and sending best wishes,

Bec

?

UTS CRICOS Provider Code: 00099F DISCLAIMER: This email message and any accompanying attachments may contain confidential information. If you are not the intended recipient, do not read, use, disseminate, distribute or copy this message or attachments. If you have received this message in error, please notify the sender immediately and delete this message. Any views expressed in this message are those of the individual sender, except where the sender expressly, and with authority, states them to be the views of the University of Technology Sydney. Before opening any attachments, please check them for viruses and defects. Think. Green. Do. Please consider the environment before printing this email.


Re: new Multiple cohesion measures

 

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Hi Steve,

Thank you so much, this is really helpful.

Best wishes,

Bec

?

?

From: ucinet@... <ucinet@...>
Sent: Monday, 18 March 2019 7:53 AM
To: ucinet@...
Subject: RE: [UCINET] new Multiple cohesion measures

?

?

Hi Rebecca, the help files are little behind. A quick description can be found here:

?

?

steve

?

?

?

From: ucinet@... <ucinet@...>
Sent: Monday, March 4, 2019 02:57
To: ucinet@...
Subject: [UCINET] new Multiple cohesion measures

?

?

Dear UCInet group.

?

I hope all is going well.

I have a query regarding the multiple cohesion measures function as a few new metrics have appeared e.g.., “Small Worldness,” “Wiener Index”, Dependency Sum”, ?“Breadth” etc.

?

I have a look in the software help and am currently unable to locate the meaning /rational of these.


Is there somewhere I can read up on these measures?

Thank you and best wishes,

Bec

?

?

?

?

?

Dr Rebecca Cunningham

Research Principal (Climate Change Adaptation)

Institute for Sustainable Futures
University of Technology Sydney
T. +61 (02) 9514?4987
M. +61 475 415 245
PO Box 123 Broadway NSW 2007 Australia

?|? |








?

?

UTS CRICOS Provider Code: 00099F DISCLAIMER: This email message and any accompanying attachments may contain confidential information. If you are not the intended recipient, do not read, use, disseminate, distribute or copy this message or attachments. If you have received this message in error, please notify the sender immediately and delete this message. Any views expressed in this message are those of the individual sender, except where the sender expressly, and with authority, states them to be the views of the University of Technology Sydney. Before opening any attachments, please check them for viruses and defects. Think. Green. Do. Please consider the environment before printing this email.

UTS CRICOS Provider Code: 00099F DISCLAIMER: This email message and any accompanying attachments may contain confidential information. If you are not the intended recipient, do not read, use, disseminate, distribute or copy this message or attachments. If you have received this message in error, please notify the sender immediately and delete this message. Any views expressed in this message are those of the individual sender, except where the sender expressly, and with authority, states them to be the views of the University of Technology Sydney. Before opening any attachments, please check them for viruses and defects. Think. Green. Do. Please consider the environment before printing this email.


Re: new Multiple cohesion measures

 

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Hi Rebecca, the help files are little behind. A quick description can be found here:

?

?

steve

?

?

?

From: ucinet@...
Sent: Monday, March 4, 2019 02:57
To: ucinet@...
Subject: [UCINET] new Multiple cohesion measures

?

?

Dear UCInet group.

?

I hope all is going well.

I have a query regarding the multiple cohesion measures function as a few new metrics have appeared e.g., “Small Worldness,” “Wiener Index”, Dependency Sum”, ?“Breadth” etc.

?

I have a look in the software help and am currently unable to locate the meaning /rational of these.


Is there somewhere I can read up on these measures?

Thank you and best wishes,

Bec

?

?

?

?

?

Dr Rebecca Cunningham

Research Principal (Climate Change Adaptation)

Institute for Sustainable Futures
University of Technology Sydney
T. +61 (02) 9514?4987
M. +61 475 415 245
PO Box 123 Broadway NSW 2007 Australia

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confused with the answer from the calculation of UCINET

 

Dear All:

I try to compare with the densities of two different networks. The result come as followings:


->dsp densitydiff(Network1Rows Netork2Rows undir)


Bootstrap SE1 = 0.1354

Bootstrap SE2 = 0.2363

T-statistic? ?= 1.3690

Cohen's d? ? ?= 1.9163


Test for equal degree centralization. 20000 iterations. Data are undirected.


? ? ? ? ? ? ? ? ? ?1?

? ? ? ? ? ? ? ?Measure?

? ? ? ? ? ? ? ?-----?

? ? 1? ?Network1 ROWS 0.506?

? ? 2? ?Network2 ROWS 0.875?

? ? 3 Obs Diff 0.369?

? ? 4? p-value 0.090?

4 rows, 1 columns, 1 levels.



I have two questions about the result.

First, the title of the result "Test for equal degree centralization.20000 iterations. Data are undirected." makes me a little confuse because I am testing the difference of density not the centralization. Why the title shows the test for equal degree centralization?

Secondly, it looks like that there is no significant difference between the two networks in terms of density.

My problem is the number of density calculated by UCINET is different from the number by hand calculation.

According to the result, the density of the? Network2 is 0.875. However, my hand calculation is only 0.0708. I don't understand what the problem come from. Can any one help me solve this confused problem.? Thanks a lot!

? ? ? ? ? ? ? ? ? ? ? Jen