Tag Archives: gephi

My Facebook network via Gephi

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Today I’ve been mapping some social networks on Gephi, and really trying to develop my knowledge of the program a bit. I wish that I’d come across this a long time ago because I do feel as though I’m rushing to take everything in at the moment, but it’s going okay for now.

I started by mapping my Facebook network. I used Persuasion’s fantastic guide on mapping Facebook networks, which has definitely been one of the most useful guides I’ve seen to mapping data on Gephi. Unfortunately, for me anyway, it’s been a bit of a mystery and has involved an awful lot of guess work to try and figure out how to use it. I’m still trying to get my head around .csv files.

I retrieved the connection data using netvizz – a Facebook app that trawls your network and pulls out all kinds of data. You’ll need to install the app to do the same (just search ‘netvizz’ within Facebook), but it’s fairly straightforward. I imported the data to Gephi as a .gdf file – make note, because this took some fiddling around with for me. I couldn’t get the file to just save as .gdf for some reason, but I eventually got there. (You might not be as new to this as I am so it might not be such a headache!).

Following Persuasion’s guide, this is what I came up with:

my facebook network connections labeled jpeg

I added the labels myself as annotations in Preview. They’re not exact, but, they’re pretty close. I’ve set the parameters to exclude anyone that has no network connections with anyone else on my list. There are a couple of people who are (technically) mislabeled here, as they might provide the most significant number of connections to others (for example, the individual that has the largest node is a friend I met in 2007, but through her I have met a lot of people since 2010, so she is in that ‘group’).

Pretty cool hey? I’m hoping to do some more updates as I have more of a play around with the program this afternoon. I’m going to try to retrieve some information about place from the data now, so hopefully there’ll be something interesting to see later on.

A fraction of Perth bloggers, in colour.

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I’ve collected in excess of 300 subjects in my list of Perth bloggers, and am up to the letter ‘F’ in plotting them. I’m using Gephi for the visualisation, and despite a rocky start (i.e. me having no idea what I was doing) I’ve now got the hang of it and it’s starting to look pretty damn cool!

Probably the craziest thing is that this list just keeps on growing – I’m probably discovering 20 new blogs a day, at least, but I’m only plotting those that are active bloggers (i.e. have posted within the last year and posted regularly before that, and user another platform – Twitter, Facebook, Instagram, Flickr, etc – as well as blogging). What that means is that there are potentially hundreds more.

Every dot on this graph represents a blogger, and every line is a link in or out of that blog (you might be able to see the tiny arrows pointing the direction). The dots change size as they attract more inward or outward links. The colours are significant too – the pink ones are fashion bloggers, the purple are food bloggers, pale blue are lifestyle bloggers, etc. This is going to change so there’s not too much point going in to it here; it’s just an easy way for me to keep track of what’s going on.

There are labels, too, so I know which dot represents which blogger, but I’ve kept them hidden to protect the identities of the geeky ;)

Including this data in my thesis in visual form is a bit of a gimmick – I could just provide a bunch of stats and numbers – but I feel that it’s really helpful to be able to see what networks look like. Not all blogs are equal, and not all share equal involvement in the blogging community. Of course, this data simply represents the network at this stage; it says nothing about the quality of content (not that I really get to be the judge of this!), how popular the blogs are (a blog may have few inward links but be read by a significant number of people, and certain genres are more generally popular than others), but it’s a good start. I’ll be doing the same thing with some other networks too, particularly Twitter, as Twitter has stolen a lot of blogging’s thunder in recent years.

Tim Highfield from Curtin has been a massive help with pointing me in the right direction on this one. Check out some of the stuff he’s done with visualisations – his look way cooler than mine.

If you’ve ended up here via Twitter…

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Hi everyone!

If you’ve ended up here via Twitter, there’s a fair chance you responded to my tweet for Perth bloggers, so I thought I’d write up a little bit about what I’m doing.

I’m in the final stages of my PhD, and writing up the thesis is… an adventure, to say the least.

Basically, I’ve been observing a whole heap of Perth blogs for the past four years with varying degrees of commitment (often not much), but as I’m nearing the final stages of writing up I really need some hard data to back up my ramblings.

That’s where you come in.

In the initial stages I’m going to compile a list of bloggers (which I will make available here if anyone is interested). Then, I’ll be looking at which other platforms they’re using: Twitter, Facebook, Pinterest, and so on.

I’m going to use a pretty snazzy open-source software called Gephi to plot the connections that exist between the people whose blogs I’ve been following. So I’ll track links between blogs, links between Twitter feeds, links between Facebook pages, etc. until eventually I should have some pretty awesome visualisations of what Perth’s online community looks like.

I will update here over the coming weeks with what is going on, but if you would like to know anything more please feel free to email me or leave a comment here.

A note about how I am using this information

I won’t be doing anything unethical with your information. Nothing will be made public that is not already public online. If you do not use your real name online, your name won’t appear online or in my thesis. I certainly will not be publishing anything like personal contact details.

If you would prefer not to be involved, just contact me and I will take you off the public list (and remove you from my research data altogether).