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Here is a quick blog post with an example of plotting the country name
co-occurrence data from below as network-over-map in R:
Seemed fairly easy, but is not doing anything sophisticated with the
edge routing like the Great Circle routes in Katherine's later posts.
On 01/26/2016 11:53 PM, Katherine Ognyanova wrote:
> Hi Skye,
> It'd be great to work out things in Statnet. I've mostly used this for
> data at the country/city level (flights, phone call volumes, hyperlink
> volumes, etc.). You have the airline data of course (that's the one
> we've used for workshops in the past). Internet Archive data with
> geocoded domains and links among them may be useful - I have to check if
> we have anything clean enough and small enough to share.
> Otherwise, off the top of my head, perhaps this: http://kateto.net/countries
> It's from a Lazer Lab + Politico project. The nodes are countries
> (geocoded with ggmap to wherever the google maps API pins them). The
> weighted links are based on country name co-occurrence in political
> documents. The visualizations use ggplot2. Oh, and we did have similar
> data at the US-only level too (state co-mentions).
> On 1/27/2016 2:09 AM, Skye Bender-deMoll wrote:
>> Hi Katya,
>> Do you have an example public network dataset with lat-long? Just the
>> airports dataset? I've tried to work up network-over-map examples with
>> the statnet packages before and had some trouble getting the R map
>> projections to work as I expected. i'd be interested in trying it again
>> On 01/26/2016 10:16 PM, Katherine Ognyanova wrote:
>>> If you happen to use R, somewhat surprisingly the best option for
>>> geo-mapping of network data I've found there is in the ggplot2 package
>>> (it takes more effort to do this within igraph or Statnet, though it is
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