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SOCNET  July 2017

SOCNET July 2017

Subject:

Re: Longitudinal social networks framework and epistemology

From:

"Kathleen M. Carley" <[log in to unmask]>

Reply-To:

[log in to unmask]

Date:

Sat, 22 Jul 2017 12:06:16 -0400

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*****  To join INSNA, visit http://www.insna.org  *****

There is also an earlier excellent book by Pat Doreian, also see the 
thesis by Ian McCulloh at CMU (which you can get by inter-library loan).

Doreian, Patrick, and Frans N. Stokman, eds. Evolution of social 
networks. Vol. 1. Psychology Press, 1997.

McCulloh, Ian. Detecting changes in a dynamic social network. Diss. 
Carnegie Mellon University, 2009.

---
See also these
McCulloh, Ian, and Kathleen M. Carley. "Social network change 
detection." (2008).

McCulloh, Ian, and Kathleen M. Carley. "Longitudinal dynamic network 
analysis: using the over time viewer feature in ora." (2009).

(note change detection is available in ORA, as are a number of other 
longitudinal techniques)




On 7/21/2017 9:22 AM, Thomas Ball wrote:
> ***** To join INSNA, visit http://www.insna.org *****
> Gloria-
> 
>     In all likelihood, the canonical resource for longitudinal network 
> analysis is that of Tom Snijders at Oxford 
> (https://www.stats.ox.ac.uk/~snijders/siena/) as well as his students 
> such as Christian Stadtfeld now at ETHZ 
> (https://www.uni-konstanz.de/universitaet/aktuelles-und-medien/oeffentliche-veranstaltungen/veranstaltungen/veranstaltungsdetails/2017/1/31/event/23366-Christoph-Stadtfeld-Zric/tx_cal_phpicalendar/). 
> 
> 
>    I hesitate in calling this work 'seminal,' although it is in the 
> context of network literature, because it's strongly related to earlier 
> work done in psychometrics on multimode principal components such as 
> PARAFAC (e.g., this tutorial, 
> https://www.cs.cmu.edu/~pmuthuku/mlsp_page/lectures/Parafac.pdf), Pieter 
> Kroonenberg's book /Three-mode Principal Component Analysis/ and his 
> 'Three Mode Company' (http://three-mode.leidenuniv.nl/), Ledyard 
> Tucker's original decompositions of the data cube 
> (https://en.wikipedia.org/wiki/Tucker_decomposition) as well as the work 
> of many scholars in longitudinal multidimensional scaling and the 
> methods they developed to decompose matrices enabling dynamic analysis 
> (e.g., https://en.wikipedia.org/wiki/Multidimensional_scaling) including 
> J.D. Carroll, William Kruskal, Wayne DeSarbo or Forrest Tucker's ALSCAL 
> -- the original alternating-least squares algorithm which continues to 
> see wide use today by machine learning enthusiasts.
> 
> Thomas Ball
> 
> On Fri, Jul 21, 2017 at 8:24 AM, Gloria Alvarez <[log in to unmask] 
> <mailto:[log in to unmask]>> wrote:
> 
>     ***** To join INSNA, visit http://www.insna.org *****
> 
>     Hi,
> 
>     I am researching about longitudinal social networks and some
>     questions came up
> 
>     1) In terms of epistemology, which is the difference between
>     "dynamic social network" and "longitudinal social network". Does it
>     come from the approach? ie. Longitudinal looks
>     associated with time-based approach and dynamic with "actor-based"
>     models? From different terminology across different disciplines? others?
> 
>     2) Is there any common framework that synthesizes all different
>     longitudinal/dynamic models/approaches? I found some in Wasserman &
>     Faust, McCulloh & Carley, Holme & Saramäki,... but I have problems
>     to located some models in those classifications and I also find
>     difficult the differences between disciplines approach (social
>     science, physics, computer science...).
> 
>     Thanks very much in advance for your support and have a nice weekend,
> 
>     Gloria
> 
>     _____________________________________________________________________ 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]
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>     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.

_____________________________________________________________________
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