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I transformed the Panama Papers dataset into Pajek's multirelational
network and I prepared an overall picture how different relations link
different types of nodes. See
http://vladowiki.fmf.uni-lj.si/doku.php?id=notes:net:pa
From this network it is easy to extract different subnetworks.
with best wishes, Vlado
On 14-05-2016 15:55, Moses Boudourides wrote:
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>
> Hello,
>
> I've been also spending some time with the Panama Papers dataset.
> However, in what concerns the network structure that could be
> extracted from this data set, it's not yet very clear to me which
> relations could be used for that purpose. The relational part of the
> dataset is the file all_edges.csv, which contains 3 columns: the first
> and the third columns contain node_ids and the second refers to the
> following five types of relations that associate a node of the first
> column with the corresponding node of the third column:
> 'intermediary_of', 'officer_of', 'registered_address', 'similar',
> 'underlying'. Apparently only the fourth type ('similar') is symmetric
> (undirected) and all the other four types are obviously directed.
>
> Given that the total number of all relations (edges) is very high
> (1265690), I was wondering what sort of aggregations among types of
> relations might simplify the complexity of the Panama papers network.
>
> I would appreciate if someone is willing to share any ideas about a
> meaningful aggregation scheme for relations. Of course, one could
> disregard any sort of relational aggregation and treat the network as
> a multilayered (multiplex) one, although the size and the complexity
> of the Panama Papers network appear to be rather restraining.
>
> I should add that, following Dmitry Zinoviev's original work on this
> dataset, at the moment, I can make a number of computations and
> visualizations for parts of the network (I'm using Python's Networkx
> and Lightning-Python for interactive visualizations). For instance,
> being motivated by what Dmitry is doing, I've managed to analyze the
> ego-networks extracted from egos which are nodes of certain type
> (officers, intermediaries, addresses, entities) associated with a
> particular country and being connected to alters according to a
> certain relationship type.
>
> For instance, this is the (symmetric) network in the case that egos
> are Greek officers and alters correspond to international entities and
> addresses (aggregated by all types of relations-edges):
>
> http://public.lightning-viz.org/visualizations/0a2669fc-f8bd-4cbf-b66f-1110f63c49df/public/
>
> (This is just an example: I can produce such ego-centric networks for
> any country in the Panama Papers data.)
>
> Admittedly, I'm not pleased with the aggregation of relations I'm
> doing here (perhaps the inclusion of addresses was redundant too) and,
> thus, I would ask for your ideas, comments or suggestions.
>
> --Moses
--
Vladimir Batagelj
IMFM - Institute of Mathematics, Physics and Mechanics
Jadranska 19, 1000 Ljubljana, Slovenia
and
University of Primorska, Andrej Marušič Institute, Koper
T: +386 1 4766 672
W: http://vladowiki.fmf.uni-lj.si/doku.php?id=vlado
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