[R] Visualization of people's interactions by participation to parties

[Clint Bowman]

Hendrik,

As a start, I'd make a matrix of zeros with the parties in rows 
and all of the participants as columns and put a one for each participant 
at each party.  The matrix will consist of a vector for each 
participant showing the parties attended. The pattern may suggest the next 
step.  Similarity of vectors could be an indication of interaction.

Clint

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On Fri, 4 Sep 2015, Adams, Jean wrote:

> Hendrik,
>
> It's not clear to me what kind of R help you are looking for.  I suggest
> you provide more information on the data that you have and the questions
> that you want answered.  Is it in an external file?  Is it an R object?
> What code have you written or tried?  Including example data, for example
> the output from dput(), is very helpful.
>
> Jean
>
> On Wed, Sep 2, 2015 at 1:46 AM, Voxcoelestis via R-help <
> r-help at r-project.org> wrote:
>
>> Dear all,
>>
>> I have a long list of parties and participants over many years and want to
>> extract network relations between people to identify groups of friends. My
>> list looks like this:
>>
>> Party 1; date party 1; first name 1 last name 1; first name 2 last name 2;
>> first name 3 last name 3;
>> Party 2; date party 2; first name 1 last name 1; first name 3 last name 3;
>> first name 4 last name 4;
>> Party 3; date party 3; first name 3 last name 3; first name 5 last name 5;
>> Party 4; date party 4; first name 2 last name 2; first name 6 last name 6;
>> first name 3 last name 3; first name 1 last name 1;
>> Party 5; date party 5; first name 5 last name 5; first name 4 last name 4;
>> ....
>>
>> Obviously the amount and the order of names is not regular. The list is
>> far too long to count co-appearances for each person-person combination by
>> hand.
>>
>> What I would like to do is first of all create a network with individual
>> persons as nodes and the co-appearances as edges and the number of
>> co-appearances as strenght of interactions clustering closesly related
>> people.
>>
>> In a second step it would be beneficial to extract information on the
>> durability of these interactions by including the time difference between
>> first and last interaction.
>>
>> Do you have any ideas or hints how to approach this problem?
>>
>> Thank you so much,
>>
>> Hendrik
>>
>> ______________________________________________
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>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
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>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>