Animated Twitter Networks

November 11, 2013
By

(This article was first published on Beautiful Data » R, and kindly contributed to R-bloggers)

In this blogpost I presented a visualization made with R that shows how almost the whole world expresses its attention to political crises abroad. Here’s another visualization with Tweets in October 2013 that referred to the Lampedusa tragedy in the Mediterranean.

#Lampedusa on Twitter

But this transnational public space isn’t quite as static as it seems on these images. To show how these geographical hashtag links develop over time, I analyzed the timestamps of the (geo-coded) Tweets mentioning the hashtag #lampedusa. This is the resulting animation showing the choreography of global solidarity:

The code is quite straightforward. After collecting the Tweets via the Twitter Streaming API e.g. with Pablo Barberá’s R package streamR, I quantized the dates to hourly values and then calculated the animation frame by frame inspired by Jeff Hemsley’s approach.

One trick that is very helpful when plotting geospatial connections with great circles is the following snippet that correctly assembles lines that cross the dateline:

library("geosphere")
for (i in 1:length(l$long)) {
inter <- gcIntermediate(c(l$long[i], l$lat[i]), c(12.6, 35.5), n=500, addStartEnd=TRUE, breakAtDateLine=TRUE)
if (length(inter) > 2) {
lines(inter, col=col, lwd=l$n[i])
} else {
lines(inter[[1]], col=col, lwd=l$n[i])
lines(inter[[2]], col=col, lwd=l$n[i])
}
}

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