#wediaczar (or “I’m getting married in the afternoon”)
July 29th, 2009
Tomorrow I’m getting married, so I probably won’t be posting for a while. Not, of course, that I’ve been posting a lot recently.
Without wanting to get sentimental (it’s not that kind of a blog, and I’m not that kind of a man) I can say that not only did I never believe that I’d find someone like Krista, but that now I have found her, I still can’t really believe it.
I’m saving the rest of what I have to say for my speech tomorrow evening. There are all sorts of little surprises planned for the day, but one of the biggest surprises right now is “what Mat will be saying in his speech” because I’ve yet to write it. Tim has told me “be nice to everyone and try not to sound like Hugh Grant.”
Anyway, the hashtag for my wedding will be #wediaczar. Given that the audience is startlingly low on digital media bods, it’s not like I think it’s going to trend or anything, but it seemed like too good a hashtag to waste.
Tags: #wediaczar
Posted in life | 13 Comments »
A first stab at a perl script to create Twitter friend/follow matrices
July 14th, 2009
Geek alert: if the title of this post isn’t a dead giveaway I should tell you — unless you’re interested in APIs and badly-put-together bits of code — this probably isn’t for you.
I’ve recently found myself using a service provided by Damon Clinkscale called DoesFollow. All it does is answer the simple question “does twitter user A follow twitter user B?” Apart from a frill which lets you reverse the order of your question (“does twitter user B follow twitter user A?”) that’s all it does. You can even interrogate it from the address bar like this: http://doesfollow.com/barackobama/mediaczar
While I was thinking about how useful a service this is, I was suddenly struck by a moment of clarity. A lot of the research I’ve been doing could be simplified by something like this.
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Tags: kludge, network analysis, networks, perl, twitter
Posted in hack, twitter | 6 Comments »
Thinking differently about word-of-mouth
June 30th, 2009
The current approach to WOM is to try to stimulate positive WOM while addressing or countering negative WOM. A sort of “accentuate the positive, eliminate the negative and don’t mess with Mr In-Between” strategy.
But what if we could do it a different way?
This idea stems from a conversation I had back in February with Martin Kelly and Andy Cocker of Infectious Media. Since that time I’ve chatted it through a couple of times with various interesting people. It’s not properly thought through yet, but following a chat a couple of weeks ago with Ketchum London’s new Head of Digital, the excellent Fernando Rizo, I’ve decided to put the idea out into the public domain to gauge what (if any) interest there is and whether I should continue to work on it.
“Word of Mouth” is hard to do well
I’ve read lots of word of mouth marketing case studies (there’s a great list over at WOMMA) and it strikes me that WOM is hard to do well for a few reasons. I don’t want to go into these in too much detail, but here are a couple of the structural issues:
- Unless I’m a journalist, an A-list blogger or media personality or have some kind of platform, I probably have a very low reach.
Despite everything pointing towards personal contact being the best impetus for positive word of mouth, most word of mouth campaigns compensate for my low reach by trying to get me to self-service my relationship with the brand and the campaign.
- “Viral” distribution just doesn’t work the way most people seem to think it does; and this is particularly true when it comes to WOM.
While I’m quite likely to tell stories about my personal experience of a brand and fairly likely to tell stories that involve a mutual friend, I’m much less likely to tell stories about other friends’ experience, and not likely at all to tell stories about friends-of-friends.
Furthermore because of the ‘clumpiness’ of most people’s social graphs, geometric progression (the “I tell two people and they each tell two people and so on” effect) just doesn’t happen.
Homophily
One of the many reasons that WOM works is a thing called homophily — which roughly translates to “birds of a feather flock together”, or “you can tell a man by the company he keeps.”
I’ve written about examples of this before: for example, my analyses of twittering US Congresspersons and Westminster MPs which showed that one can predict with some reasonable degree of accuracy the political colouration of any given twitter account based on their mutual friends and follows (if you want to know more about the methodology, it’s worth reading Robert Hanneman’s chapter on cliques and subgroups.)
But there’s another side to the homophily coin; the social pressure to conform to the group’s norms.
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Tags: influence, influence mapping, marketing, network analysis, public relations
Posted in influence, networks | 8 Comments »
Today’s “Integration Triangle” presentation
April 15th, 2009
These are the slides from a presentation I did this morning on the topic of the Integration Triangle. I’ve talked about this here before in the article “5 Straightforward Ways To Integrate Your Communication Activities” — this includes some quick case studies.
I created these slides to support the presentation I was giving: they aren’t the presentation itself. This means that while you’ll be able to have a good guess at what I was saying most of the time, there will be moments when my meaning is opaque.
There are 70 slides in the presentation, including the front and back cover. Nevertheless, I gave the presentation in under 25 minutes. To save you doing the maths, that averages out at around 3 slides every minute (actually, there was a 4 minute delay in the middle of the presentation — so it’s more like 3-and-a-half slides per minute.)
In fact, my slides fall into two categories — those on which I spend fewer than 5 seconds, and those on which I spend more than a minute. This is more an artistic decision than anything else — I think that lots of slides going past very quickly give an appearance of pace and energy (which I dearly need first thing in the morning), but can rapidly become exhausting to watch and hard to follow without the occasional pause for breath.
Even with 70 slides, there’s so much more that I can say about the “Integration Triangle” as a planning tool — but I was trying to keep this to a single simple message. I’m hoping that (whatever they thought about my presentation, and no matter whether they liked it or believed what I was saying) the audience will remember what it was that I was saying, and be able to tell a version of the story themselves.
There’s just so much that we can talk about when it comes to the whole Digital PR thing that it all becomes rather overwhelming. I’ve just got off the phone to a colleague in Vienna (where I’m speaking next week) who wants me to talk to his audience about “Facebook and Twitter and Blogs” (oh my!) And I’ve got 45 minutes to do this. Of course I can do it. But what on earth is the “one thing” I want them to remember?
Tags: get on board, life's for sharing, orange, presentation, rockcorps, t-mobile, wwf
Posted in opinion, porter novelli | 2 Comments »
Methodology and thoughts behind those PR Week Twitter stats
February 26th, 2009
There’s a school of thought that says that what’s important in social media is to attempt to create debate, not consensus.
Peter Hay from PR Week and I appear to have been rather successful in this. This morning, PR Week published an article, Twitter has suddenly exploded. Almost immediately, Twitter (or at least our particular neighbourhood of Twitter) suddenly exploded.
One or two people were rather scathing: suggesting that the stats demonstrated that Peter and I didn’t understand the “essence of Twitter” or that they were “obviously flawed”, or that we had “redefined shallow”.
Indeed (horror of horrors) some people even went so far to suggest that Porter Novelli had ginned up the results to put us at the top. In fact, in PR week’s list, we came second. But no doubt this was a Machiavellian ploy — it’s details like those, Pooh Bah would say, that “give artistic verisimilitude to an otherwise bald and unconvincing narrative.”
I joke, but I can completely understand people’s strong feelings about this; PR Week was torn between a desire to cover our approach (and give credit where appropriate) and a need to keep the article readable and relevant to the greater proportion of their readers.
I’d like to share our methodology with you all so that you can repeat our experiments, should you so wish. After that, I’ll talk about the methodology that we were originally going to follow,
Tomorrow (once it’s had a chance to blow over), I’ll post some quick thoughts on the whole storm-in-a-Tweetcup thing.
Methodology
We used Michael Litman’s (@litmanlive) list of UK Media Tweeple. This was based on original work by Stephen Davies (@stedavies) but has been wikified so that agencies can (should they so choose) keep their information up to date.
Lots of people on the list were pretty borderline — there are in-house teams and vendors there, as well as agencies with a significantly broader remit than simply “PR”. I am a relative newcomer to the world of PR, and was more than happy to let PR Week define who is PR and who isn’t, but we erred on the generous side. We are Social, for example, made the cut to be on the research list.
Had we had the time, I’d have sent a note out over Twitter asking everyone to update their entries. Time, however was not on our side, and I didn’t even get around to hinting at what I was doing until the evening of the 23rd.

By then though it was already clear that I had a large job on my hands; there were almost 350 people on the list. On the whole, the UK PR community should be proud of how quickly it has reacted to the whole “Twitter thing”.
I took the list, published it as a Google Spreadsheet and — using a Yahoo! Pipe that I adapted for the purpose, queried the Twitter API for the summary data on each account on that list.
Twitter gives you all sorts of interesting information, but what we were grabbed were the following:
- Date joined Twitter
- Number of Friends
- Number of Followers, and
- Number of Updates.
That allowed us to create this spreadsheet, from which the stats mentioned in the PR Week article were taken.
Again, Porter Novelli took no part in the editorial decisions (although they seem pretty straightforward.) You will recall that Peter and Gemma were writing for a general readership, not for the Twitterverse!
Methodology we’d like to have used
Those of you who’ve read my blog before will know that my real interest in Twitter is more complex than the previous methodology would suggest. When Peter and I first discussed the exercise on Monday we had been hoping to do something more along the lines of the network analysis that we’ve been fiddling with at Porter Novelli.
Here are some points to bear in mind.
First of all, not all followers are created equal. If I have only ten followers, but they each have a thousand followers, that may mean I have more opportunity-to-influence than if I had a hundred followers with only ten followers each.
More to the point, the fewer people those ten people follow themselves, the more influence I wield within their networks (if I am one of only ten people they follow between them, I will have greater share-of-voice than if I am merely one of ten thousand.)
Secondly, the followers whom I don’t share with the rest of the network count for more than those who follow several (or many) of my peers. The more “exclusive” my follower-base, the greater my control over on the flow of information within the overall network, and the greater my value to the network.
I’ve been doing some work looking at unduplicated reach among twitter networks. For example, looking at Porter Novelli’s own global Twitter footprint, it was interesting to see how many of our contacts were duplicated.
So what Peter and I really wanted to do was to use some of these techniques on the PR Week data set. For those of you with a mathematical (or social network analytical) bent, we were going to run some eigenvector shizzle on the whole bizzle. Oh — and look at unduplicated reach for the various companies on the list.
What went wrong?
It was always an ambitious project. The 344 people who were under analysis had a fairly daunting 95K followers between them. The Twitter API lets you make 100 requests an hour, and each request returns data on up to 100 followers. Even if we were to assume that everyone had followers in nice tidy multiples of 100 (they don’t) then it would have taken 9.5 hours to download the data using one Twitter login.
The trick of course, is to use more than one login. Tim Hoang (@timhoang) and I quickly registered 50 temporary accounts to power the API requests. Twitter’s terms have historically been quite relaxed about this sort of thing, and we’ve always been very careful to try and stay within the spirit of those terms.
But.
Twitter has been hit lately by a bunch of bad things (like spam bots and pyramid schemes), and they’re tightening up their defenses. This past weekend, they’ve tightened up a lot, and things that used to be fine just aren’t.
We managed to collect information on only around 60K followers out of the 95K. This was too large a margin of error to correct (although we made several attempts to do so).
So — we had to abandon our grand plans, and revert to the simple counts approach (as detailed above.) This won’t stop us trying to improve our processes, but we’ll need to talk to Twitter about that.
Some thoughts
Kate Hartley from Carrot Communications (who sits with me on the PRCA’s Digital Working Group) joked that it’s strange how PR people create research-for-news-stories for their own clients on a daily basis, but are miffed when their own techniques are used against them. At one level, I agree with her — I think that some people are probably disappointed that they aren’t the ones with their names on the research.
But there’s more to worry about than that. Here are my thoughts.
- For God’s sake get over yourselves! We’re talking about Twitter here, not the economy. Worry about something important, why don’t you? I still can’t get over the fact that — when a pilot managed land an airplane on a river, the story we all tell each other is “how it broke on Twitter.” What — the story’s not about a man who magically landed a f*cking plane on a f*cking river? Are we really getting this right?
- How influential you are on Twitter is not a real thing. It doesn’t really matter how many Twitter friends you have (although I’ve now got heaps, thank you very much!) Context is everything. My boss, who runs Porter Novelli’s EMEA network and sits on our Executive Committee is on Twitter. She is more influential than I, and will continue to be, no matter how many Twitter followers I accrue.
Twitter is just one channel through which exercise your influence. Don’t give up on your blogs, your Facebook pages, your Amazon reviews, or your Last.fm playlists or your IM friend lists, for God’s sake. But remember, it’s who you are, and your relationships that matter; your “context”, and not your “counts.”
- The really interesting question isn’t “who are the Twitterati” or twitter influencers. I’m interested in the Twitter thing mainly because I want to see how well it reflects real life. After today, I’d probably say that it doesn’t very well, wouldn’t you?
Be warned — I may just follow this research up with some research on “how many phone numbers PR people have on their mobile phones.”
Tags: pr week
Posted in pipes, porter novelli, twitter | 21 Comments »
Swedish Politicians on Twitter
February 22nd, 2009
Twixdagen does for Swedish politics what Tweetminster does for British. Hampus Brynolf (@hampusbrynolf) just sent me a link to this map he’s pulled together for their blog:
You’ll need to click through to his blog post to experience and interact with the map properly.
Hampus says that he used aiSee to generate an SVG file which could then be opened in Illustrator to “search and replace” on shapes, colors and lines (which explains the good-looking graph.)
Tags: aisee, mapping, network analysis, networks, politics, sweden
Posted in networks, twitter | 2 Comments »












