|
***** To join INSNA, visit http://www.insna.org *****
Hi
You lent me a MAC adapter on Tuesday at Sunbelt. Thanks you!!!!!
I have not being able to locate you.
If you are still in Brighton Beach please contact me.
Thanks
Silvia Dominguez, PhD, MSW
Chair- Race and Ethnic Minorities ASA
Associate Professor
Sociology & Human Services
Center for International Affairs and World Cultures
<http://www.northeastern.edu/international_center/>
Renaissance Park 210N
Northeastern University
Boston, MA 02115
[log in to unmask]
Mixed Methods Social Networks Research: Design and Applications.
<http://www.cambridge.org/us/academic/subjects/sociology/research-methods-s
ociology-and-criminology/mixed-methods-social-networks-research-design-and-
applications>
Getting Ahead: Social Mobility, Public Housing and Immigrant Networks.
<http://nyupress.org/books/9780814720783/>
"Nothing in all the world is more dangerous than sincere ignorance and
conscientious stupidity." MLK.
SPAšs or Self-Propelling Agents rule the world!!!
On 6/26/15, 12:40 AM, "Mahin Raissi" <[log in to unmask]> wrote:
>***** To join INSNA, visit http://www.insna.org *****
>
>Hello,
>I have a similar question to what Seok-Woo has asked: is there any way
>to compare node level centrality scores, across ego-networks with
>different sizes and densities?
>One approach can be: using ranked centrality scores. For each
>ego-network, I calculate the centrality scores for all nodes (e.g.
>betweenness), rank them and then normalize them; the resulted score for
>each node will be something between 0 and 1.
>
>I am looking for suggestions on this question and the proposed approach.
>Do you think it is an appropriate way to solve this problem?
>Any comment or help is appreciated.
>Regards,
>Mahin
>
>------
>Mahin Raissi
>PhD Student
>Australian Demographic and Social Research Institute (ADSRI)
>Coombs 9, Australian National University, ACT 0200, Australia
>
>
>
>
>-----Original Message-----
>From: Social Networks Discussion Forum [mailto:[log in to unmask]] On
>Behalf Of Vincenzo Nicosia
>Sent: Sunday, 8 February 2015 5:14 PM
>To: [log in to unmask]
>Subject: Re: [SOCNET] comparing centrality scores across networks
>
>***** To join INSNA, visit http://www.insna.org *****
>
>On Sun, Feb 08, 2015 at 12:02:44AM +0000, Thomas William Valente wrote:
>> ***** To join INSNA, visit http://www.insna.org *****
>>
>> Seok-Woo
>> The major centrality measures, degree, closeness and betweenness, all
>>have a nodal version and a normalized one which corrects for the network
>>size. For example, degree centrality can be a count of the number of
>>links for each node (the nodal version) and the count divided by network
>>size minus one which is the maximum possible degree score for any
>>network. This latter measure is the normalized degree centrality and
>>can be compared between different networks and it ranges from zero to
>>one. If the networks are approximately equal there should be no
>>problem making such comparisons. However it is conceivable that there
>>is an association between centrality and network size in the sense that
>>it may be possible to have very central nodes in very small networks but
>>unlikely in large ones. For example, a team of 10 people may readily
>>agree who is the most popular or who is a natural leader, but a group of
>>100 or a 1,000 would have considerably more variability on who is the m!
>
> os!
>> t popular.
>> UCINET readily provides these measures.
>
>Hi,
>
>If I can add my humble opinion to the discussion, I would personally
>refrain, at least in general, from comparing the values of node
>centrality in different networks. In most of the cases, it is not just a
>matter of number of nodes. Just to make an example, two nodes may have
>the same normalised degree centrality in two different networks, but if
>the two networks have different edge densities then the normalised degree
>does not tell the whole story. And IMHO a direct comparison of the values
>of node centralities is even less grounded if we move to eigenvector
>centrality, betweenness, closeness and so forth, especially when the
>networks are large, have different sizes/order, and/or heteregeneous
>degree distributions.
>
>Nevertheless, in some special cases, namely when the networks have
>exactly the same size because they represent different kinds of
>relationships among the same actors, comparing the rankings induced by a
>given centrality measure (not just the bare values) on different networks
>can be OK.
>
>My2Cents
>
>Enzo
>
>--
>[ Enzo Nicosia - School of Mathematical Sciences - Queen Mary UL ] [ --
>v.nicosia [at] qmul.ac.uk -- katolaz [at] yahoo [dot] it -- ] [ -- web
>@QMUL: http://maths.qmul.ac.uk/~vnicosia/index.html -- ] [
>twitter:@KatolaZ -- jabber:[log in to unmask] - skype: katolaz ]
>
>_____________________________________________________________________
>SOCNET is a service of INSNA, the professional association for social
>network researchers (http://www.insna.org). To unsubscribe, send an email
>message to [log in to unmask] containing the line UNSUBSCRIBE SOCNET
>in the body of the message.
>
>***** To join INSNA, visit http://www.insna.org *****
>Hello,
>
>I am wondering if I can compare centrality measures across networks. For
>example, node A from network 1 has a centrality score of 3 and node B
>from network 2 has a centrality score of 1, (and the two networks are not
>related and different in size). Can I still conclude that A is more
>central in network 1 than B is in network 2? Or does this depend on what
>kinds of centrality we are talking about?
>
>Also, if this conclusion is misleading, is there a normalized centrality
>score that can be compared across networks? I am hoping someone on this
>list can help.
>
>Thanks.
>
>==============================
>Seok-Woo Kwon
>Assistant Professor
>Dept. of Strategic Management
>Fox School of Business
>Temple University
>544 Alter Hall
>1801 Liacouras Walk
>Philadelphia, PA 19122
>
>[log in to unmask]
>
>_____________________________________________________________________
>SOCNET is a service of INSNA, the professional association for social
>network researchers (http://www.insna.org). To unsubscribe, send
>an email message to [log in to unmask] containing the line
>UNSUBSCRIBE SOCNET in the body of the message.
_____________________________________________________________________
SOCNET is a service of INSNA, the professional association for social
network researchers (http://www.insna.org). To unsubscribe, send
an email message to [log in to unmask] containing the line
UNSUBSCRIBE SOCNET in the body of the message.
|
