***** To join INSNA, visit http://www.insna.org ***** Jurgen and Jamie have already provided excellent answers. I’m only adding on additional/alternate terminology.

The 2-mode network you describe is a bipartite network with two node types: one for groups, and one for people. In that construct, people can only be connected to groups, and groups can only be connected to people (edges between person-to-person or group-to-group are not allowed). You can represent this type of network using the edge list format Jurgen suggests really easily. E.g., a group is always in column 1 and a person is always in column 2 for example would ensure your format is right for a bipartite graph.

From there, you can project your data either way, to a Group-Group network or a Person-Person network where a group is connected in the projected graph if they share a person in the bipartite graph, or two people are connected in the projection to person-person if they have a common group in bipartite. 

Python’s NetworkX package has several projection functions in its bipartite module that you play with these networks.

Good luck!

-Cody
_________________
Cody Buntain, PhD
Postdoc, @NYU/UMD
Intelligence Community Postdoctoral Fellow

On Jun 14, 2018, at 1:21 PM, Juergen Pfeffer <[log in to unmask]> wrote:

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Matrix is fine an can be imported in most tools.
However, I prefer edge lists, i.e.:
Group A       Individual 1
Group A       Individual 2
Group B       Individual 1
Advantages:
- This is normally the way we collect data
- A line per edge allows for more edge attributes (additional columns)
- More compact for sparse matrices
- Easier to handle for large networks
 
In any case, this gives you a 2-mode network. Transform it to a 1-mode (easy in any tool) and you’ll get your Group-Group network. There are different approaches how to “count” co-occurrence of Individuals. You can sum them. Or you can weigh them, e.g. if I1 and I2 are just in G1 this might bring more “points” for G1 than I1 and I2 being everywhere. But this part should be derived from your questions. What do you want to analyze with this co-occurrence?
 
 
Von: Social Networks Discussion Forum [mailto:[log in to unmask]] Im Auftrag von Aaron Guest
Gesendet: Thursday, June 1
4, 2018 6:51 PM
An: [log in to unmask]
Betreff: [SOCNET] Question About Data Entry Format
 
***** To join INSNA, visit http://www.insna.org *****
Hello Everyone,
 
This may be too simple and I may be overthinking it but I was hoping to get some feedback on the best way to manage some data. I have individual records where everyone is a member of two to three groups. There is a total of about 30 groups people can be a member of, but each is a member of at least two.
 
Now, we are not necessarily concerned about the individuals, but we need them to show the connection between the groups. We are really interested in the number of connections between the 30 groups and identifying areas of overlap and possible intervention to encourage collaboration among the silos.
 
Currently, the data looks a little something like this:
(Example 1)
 
Group A
Group B
Group C
Group D (…etc)
Individual 1
0
1
0
1
Individual 2
1
1
0
1
Individual 3
0
0
1
0
 
One idea someone suggested was to alter the data as (example 2)
 
Group A
Group B
Group C
Group D (…etc)
Group A
1
1
1
1
Group B
1
0
0
1
Group C 
1
1
1
1
 
 
 
 
 
 
The challenge with this is that Group A could have 100-200 individuals who are a member of group A and group B.
 
Is the data in example 1 the best way to handle it? Or is there an obvious solution I am blanking on right now?
 
Thanks for any help-
 
Aaron Guest, MPH, MSW, CPH
PhD Candidate in Gerontology
Graduate Center for Gerontology | University of Kentucky
Multi-Disciplinary Science Building | 725 Rose Street, Room 448   
864.617.9621 | [log in to unmask]
 
 
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