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Dear Michał,

That's an interesting working paper. You say in your email that the E-I 
index does not seem to be optimal. On which do you base this? Is it 
equivalent to one of the indices you study in the working paper?

What about network autocorrelation measures (Geary, Moran) in the case 
of 2 groups?

Best wishes,
Tom

============================================
Tom A.B. Snijders
Professor of Statistics in the Social Sciences
University of Oxford
Professor of Statistics and Methodology
Department of Sociology,
University of Groningen
for addresses and telephone numbers:
  see http://www.stats.ox.ac.uk/~snijders/

On 17/01/2014 12:42, Michał Bojanowski wrote:
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> Sender:       Social Networks Discussion Forum <[log in to unmask]>
> Poster:       =?ISO-8859-2?Q?Micha=B3_Bojanowski?= <[log in to unmask]>
> Subject:      Re: Clustering of networks / comparison across organisations
> -------------------------------------------------------------------------------
>
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>
> Dear Kerstin,
>
> E-I index does not seem to be optimal for this task. I presume the
> network is directed, given that I would use Coleman Index. You should
> find more information on these two and other aporoaches in the
> following working paper:
> http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1873465
>
> Best wishes,
> Michal
>
>
> On Fri, Jan 17, 2014 at 1:03 PM, Kerstin Sailer <[log in to unmask]> wrote:
>> ***** To join INSNA, visit http://www.insna.org *****
>> Dear All,
>>
>> I would like to do a comparison of different organisations and their network
>> structures (nodes are people, ties are frequency and usefulness of contacts,
>> sizes vary significantly from n=100 to n=1000; data is survey-generated; key
>> question was to identify the top 25 contacts from a list of everyone in the
>> organisation and then give details on these contacts).
>>
>> One of the metrics I would like to compare (and where comparison is not
>> straightforward at all, hence my email to ask for help / advice) is the E-I
>> index, i.e. the degree to which contacts are within teams or across teams.
>>
>> The difficulty is that team sizes and numbers of teams within an
>> organisation differ so much. For instance if organisation A has 10 teams of
>> 10 members each, every participant would have to nominate members from
>> outside their team to come up with 25 top contacts, hence the degree of
>> external contact might be higher by default than for an organisation B with
>> 2 teams of 50 members each, where each participant could possibly nominate
>> all 25 top contacts within their own team.
>> This is further complicated by the fact that not everyone participated in
>> the survey (i.e. missing ties), that not everyone nominated 25 people (most
>> people don't count and just use this as a rough guideline, or insist on
>> nominating fewer or more), so outdegree is not always 25 for each member and
>> of course this could vary by team as well (so members of one team, e.g. HR
>> might nominate more people disproportionately if compared to the
>> organisation's average because of their outreach role).
>>
>> Now, if anyone has come across any discussion of those problems in the
>> literature, or anyone mathematically minded on the list has an idea on how
>> to normalise these metrics so that they become comparable, I'd be very happy
>> to hear about it!
>>
>> Thanks in advance!
>> Best,
>> Kerstin
>>
>> --
>> Dr Kerstin Sailer
>> Lecturer in Complex Buildings
>>
>> The Bartlett School of Graduate Studies
>> Faculty of the Built Environment
>> University College London (UCL)
>> 14 Upper Woburn Place
>> London WC1H 0NN UK
>>
>> T: +44 (0) 20 3108 9031
>> E: [log in to unmask]
>> W: http://www.bartlett.ucl.ac.uk/graduate
>> W: http://www.bartlett.ucl.ac.uk/people/?school=gs&upi=KSAIL15
>>
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