mediaczar

A couple of weeks ago, I asked a bunch of people to send me their OPML files (for those of you who aren’t aware, an OPML file is what tells your RSS reader what feeds you’ve subscribed to — it can act as a way of moving your subscriptions between readers.) Some of the more trusting among them agreed, and that gave me the raw material for the first bit of my experiment.

Some red herrings

Along the way I uncovered a couple of things that were interesting but not (entirely) relevant to the experiment.

1. Some people are cagey about sharing their list of feeds: whether they consider it intellectual property, or whether they think that it may be too revealing, I don’t know.
2. Lots of people said things like “oh — my RSS reader? Haven’t looked at that in a while. I get all my news off Twitter these days.”

Continue reading ‘The #interestingOPMLexperiment (stage 1)’

This is a follow-up post to Why doesn’t the Tory MP have Twitter friends? — a report on some early research into the interrelationships between the few Westminster MPs who are on Twitter.

According to Tweetminster, the number of UK MPs on Twitter has doubled since this time last month. Where there were eight Twittering MPs, there are now sixteen. Here’s the map that shows who follows whom (the labels may be too small to read — if you want to see a larger image, click on the map.

I’ve coloured each node to show party affiliation; for those of you who are unfamiliar with British politics, Labour (our left-of-centre party) shows up in red, Conservatives (our right-of-centre party) in blue, and Liberal Democrats (what it says on the tin) in yellow.

The size of each node represents the individual’s “betweenness centrality” — a network analysis term that helps us place a value on individuals within a network. To give you a sense of what it means, the higher the betweenness centrality of an individual, the greater the impact when you take them out of the network. For those of you who work in large companies, it may be worth noting that senior management’s personal assistants generally have very high betweenness — something that is mostly remarked upon when they go on holiday (simultaneous translation: “take a vacation”.)

So far so good. By now, regular readers will probably be kissing their teeth and thinking “so what?” I’ve done a lot of these Twitter maps in the past and the novelty must be wearing off on you by now.

So here’s the thing. There are a few network analysis techniques that let one identify cliques and factions. What we’ve got here is a small set where we already know what people’s affiliations should be. How interesting, I thought, would it be to see how well the calculated result fits the real world data? Here’s what I found:
Continue reading ‘Can we calculate party affiliation? (The Westminster edition)’

Three weeks ago (and at the prompting of my colleague Eddie Garrett who heads up Porter Novelli DC’s digital team) I mapped out the interconnections between US Congress Tweeters. We’d been working on a Twitter crawler and it seemed like a good opportunity to test things out on a new data set.

This is a follow-up post. Once again it was prompted by a third party: Christie Findlay at Politics Magazine asked whether it would be OK to print a copy of one of the maps in their March edition. I’ve heard that three weeks are a long time in politics, so I thought I’d better run the crawl again just in case. Also I’ve got a new crawler that uses the proper Twitter API (I can see some of your eyes glazing over you know. Just skip ahead when that happens.) I’d tried it out on the Porter Novelli data set, but welcomed a chance to try it on something more meaty.

So yesterday morning before work I ran the crawl. I use the excellent Tweet Congress as my source of information about which congress people are on Twitter.
Continue reading ‘Republicans still outperforming Democrats on TweetCongress’

Three days after my last map, and after lots of internal nudging from our CMO Marian Salzman, her two helpers Tikva Morowati and Zeenat Duberia and local activists like Juriaan Vergouw, Burçu Kaptan, and Umut Ersoy, the map of Porter Novelli people on Twitter looks very different. (You can click on any of the maps in this post to go to their Flickr page where you can choose to see them at larger sizes.)
Continue reading ‘Map of Porter Novelli people on Twitter on 20th Jan 2008′

Marian Salzman (our Global CMO here at Porter Novelli) has had the inspired idea of getting people in the agency to tweet about the most exciting story this week (probably) — the inauguration of Barack Obama

You can see the results of the experiment on her blog.

I’m all for this, of course, for several reasons:

1. It gets new people onto Twitter
2. It helps us create a stronger network among Porter Novelli twitterers
3. It means I can track who at the agency is on Twitter

Continue reading ‘Map of Porter Novelli people on Twitter on 17th Jan 2008′

This is a map of the current US congressmen and women who are currently on Twitter (you can click it to see a bigger map where you can read the names.) The direction of the arrows show who follows whom, and the size of the blobs indicates how “popular” a given congressperson is among their twittering peers (where “popular” means something like “is followed by many of their peers.”) Colours indicate party affiliation (for those of you who — like me — don’t live in the ‘States and who — like me — need reminding from time to time, the Democrats are the blue dots.)

Network of US Congress twitterers showing citation frequency. Click for bigger.

A cursory glance at this map shows a few things:
Continue reading ‘Network map of US Congress twitterers’

This is a map of the eight Westminster MPs who are currently on Twitter, and the relationships between them. The larger the blob, the more followers they have among their peers. Apparently they’re a fairly clubbable lot, all – that is – except for Grant Shapps who (it seems) currently has no MP friends on Twitter. I’d say that it’s early days yet, but Mr Shapps appears to have been broadcasting since March 9th 2008. That’s an age in Twitter years. In that period, he has replied to 5 people out of a total of 249 tweets. Lots of people have tried to reach him.

I think that it’s nice that he’s so busy (after all, he has a constituency to run and a government to topple) but do think that if he’s going to do this, he ought to pay a little more attention.

Who (other than each other) are MPs most likely to follow? If we wanted to get a story in front of their noses, who would we most want to talk to? Here’s the list. Tweetminster is like Tweetcongress but with more tea and scones and fewer public representatives. The ubiquitous Stephen Fry is in place, of course. It wouldn’t be Twitter without him.

Thanks to IBM’s Many Eyes service it’s relatively simple to create complicated visualizations that my current version of Excel can’t handle. For example, this “matrix chart” that I built using Excel’s bubble chart function is clearly unacceptable. I can’t easily link statements or values to the X and Y axes, and there’s lots of overlapping that seems (after many attempts) to be impossible to fix.

Matrix chart built using Excel

I’ve published the first dump of survey and “blog metrics” data from the blogger questionnaire as a spreadsheet on Google Docs. Many, many thanks to all of you who volunteered your information.

Please feel free to use this as you see fit for your own projects. I’ve anonymised this data (just because it’s best practice, not because I think any blogger would be mortally offended by having the world know what inspires them to blog!)
Continue reading ‘Blogger typology: quantitative analysis step 1′