Suppose you’re just starting out on Tumblr. How to build your audience in the most efficient way? Obviously, you would want to reach the people who belong to the communities that would be more likely to repost the kind of content. It’s even better if you can also find the main hubs. Using a bit of network data mining and Gephi visualization tool all this can be done in a few minutes and we’ll show you how.
We visualized Hamlet’s “to be or not to be” as a text network and then read it again using Alexis Jacomy’s GexfWalker. Whether it is a new reading of Shakespeare’s classic or a bunch of unrelated words is for you to decide, but at least it allows for polysingularity of text to be expressed more fully through following the word relations while staying loyal to the text’s original structure.
Italo Calvino once said that “writing is essentially a combinatorial exercise” and that “reading is a way of exercising the potentialities contained in the system of signs”. We propose a new way of reading using text network visuaization. It goes beyond the normal sequential organization of textual material and instead offers the reader to navigate through polysingularity of meanings present within the text. Created using Alexis Jacomy’s GexfWalker and Gephi software.
In this post we demonstrate how one can detect and analyze the most influential communities and hubs in any Facebook network using Gephi and netvizz applications. We also show how network analysis can be used to identify the strong and weak sides of the network, predicting its possible future development and showing the strategies that could lead to its more sustainable development. We use the real Facebook groups created to support the protest against rigged elections in Russia in December 2011.
Together with Jan Ritsema from Association PAF we started a platform to promote what we call a “radical school change” – a learning revolution to change the school into something else.