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SOCNET  October 2015

SOCNET October 2015

Subject:

Re: Literature review of approaches to select the window size for analyzing longitudinal social networks

From:

Mason Alexander Porter <[log in to unmask]>

Reply-To:

Mason Alexander Porter <[log in to unmask]>

Date:

Fri, 16 Oct 2015 09:24:13 +0100

Content-Type:

TEXT/PLAIN

Parts/Attachments:

Parts/Attachments

TEXT/PLAIN (151 lines)

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

Re: No golden rule: that's true. It is an active area of research.

Re: may slice and dice the way you wish: oh no, that couldn't be further 
from the truth; people do things to take "simpler" approaches, but that is 
fraught with difficulties

You need to be really, really careful --- and at minimum compare your 
results for different arbitrary choices and see which qualitative features 
are similar across different choices and which are not. You want to find a 
property of the network, not an artifact of your slicing and dicing. 
Ideally, one wants to be more systematic.

Also, there are quite a few distinctions to make: something longitudinal 
that comes in discrete waves of measurements, "continuous" time series, 
event-based time series, etc. Things in different temporal windows aren't 
in general independent of each other, so a temporal network structure rather 
than sequences of static networks can be important, for many situations 
windows of the same size cause lots of problems (think of how inter-event 
times can be dsitributed in social systems, etc.). Often people 
(myself included) do some chopping in a simple way and try different ways 
that are also ad hoc to see how the answers change, but ultimately one 
really should be more principled. There is work on animal social networks 
by Yannis Psorakis and others (in Psorakis's PhD thesis at Oxford ... 
available on Stephen Roberts' website if nowhere else ... not sure if 
it's in a paper) in which they do some nice event-based clustering to 
avoud using uniform windows. In their example, there is clustering in time 
near when the birds feed (at different locations, etc.).

Note that I tend to use the word "longitudinal" in a more specific way 
than "temporal" more generally. So I would not consider things like 
citation networks to be longitunial because it doesn't come in specific 
waves (like surveying the new freshman on the first day of school each 
year to collect social data that way)

There is some discussion of chopping up temporal networks in Holme's 2015 
review on temporal networks (though it doesn't focus on social contexts, 
so you'll also want to look in other sources):

 	http://arxiv.org/abs/1508.01303


I don't know of the desired really thorough discussion of the different 
approaches with advantages, pitfalls, and other related things.

-----
Mason



> ------------------------------
>
> Date:    Fri, 16 Oct 2015 12:37:11 +0900
> From:    "Gohar F. Khan" <[log in to unmask]>
> Subject: Re: Literature review of approaches to select the window size for analyzing longitudinal social networks
>
> --047d7b2e4ab61b8dbf0522308561
> Content-Type: text/plain; charset=UTF-8
> Content-Transfer-Encoding: quoted-printable
>
> *****  To join INSNA, visit http://www.insna.org  *****
>
> Dear Shahadat:
>
> Earlier I had posted a similar query to the list, though it was related to
> scientific collaboration networks extracted from the Web of Science
> database. From the responses it seemed that there is no single golden rule
> and you may slice and dice the data the way you like. It can be either year
> by year basis, every four years, every five years, or every 10 years (it
> may depend on your research settings).
>
> These two studies may provide some clues.
>
> Howard D. White, Nancy Nazer, and Barry Wellman (2004) "Does Citation
> Reflect Social Structure? Longitudinal Evidence from the 'Globenet'
> Interdisciplinary Reserach Group", [Journal of the American Society for
> Information Science and Technology 55, 2 (January 2004): 111-26.]
> http://homes.chass.utoronto.ca/~wellman/publications/citation/jasist_55(2)_=
> pp111-126.pdf
>
> Loet Leydesdorff, Thomas Schank, Andrea Scharnhorst, & Wouter De Nooy,
> Animating
> the development of *Social Networks *over time using a dynamic extension of
> multidimensional scaling
> <http://www.leydesdorff.net/socnetw/paper/index.htm>. *El Profesional de la
> Informaci=C3=B3n* 17(6) (2008) 611-626.
> http://www.elprofesionaldelainformacion.com/contenidos/2008/noviembre/04.pd=
> f
>
>
> I hope this helps.
>
>> Dear SOCNET users,
>>
>> At present I am conducting a literature review of approaches to select th=
> e
>> right/correct window size for analysing a given longitudinal social
>> network. I did not find many articles in this respect in the present
>> literature. In fact, I did not find any approach/method that can determin=
> e
>> an appropriate window size for analysing longitudinal social networks.
>>
>> Can anyone help me in this regard!!
>>
>> Regards
>> Uddin
>> _____________________________________________________________________
>> 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.
>
>
>
>
> --=20
>
> Gohar Feroz Khan, PhD
>
> Adjunct Faculty & Research Adviser
> Korea Advance Institute of Science & Technology (KAIST)
> Global Information and Telecommunication Technology Program (ITTP)
> 291 Daehak-ro, Yuseong-gu, Daejeon, South Korea.
>
> ---------------------------------------------------------------------------=
> --


-----
Mason

----------------------------------------------------------------------------
  Mason A. Porter
  Professor of Nonlinear and Complex Systems
  Oxford Centre for Industrial and Applied Mathematics
  Mathematical Institute, University of Oxford

  Homepage: http://people.maths.ox.ac.uk/porterm
  Blog: http://masonporter.blogspot.com
  Twitter: @masonporter
  Skype: tepid451
  ----------------------------------------------------------------------------
  "I will be the lion." (Me)
  ----------------------------------------------------------------------------

_____________________________________________________________________
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