On Monday evening I was in Vienna. Thanks to our partner agency IKP Porter Novelli I had the opportunity to talk to some of the best and brightest businesses in Austria.

The presentation was given in a fabulous private salon (Austrians seem to be keen on the “private” thing — perhaps because it helps them get around the EU smoking ban) which promised “Guten Wein mit Wirtschaf, Politik & Kultur.” I don’t know where my presentation fit in.

As we were going up the stairs I saw signs that my presentation had been advertised under the title “Facebook, Twitter & Co”, so I carefully changed the title of the presentation accordingly. The bits behind the title page never really changed.

If you’ve read the Integration Triagle presentation post, then the last third of what follows will be familiar and I suggest that you stop reading when you see Arnold Schwarzenegger for the second time.

I really need to credit Paul Mead, MD of VCCP Search for the meat of the first third of the presentation: it’s pretty much a facsimile lift from an inspirational presentation I saw him give a few months ago that has changed the way I’m thinking about Social Media planning. Thanks, Paul!

After the presentation, the IKP Porter Novelli team took me out for drinks. The next day for breakfast, they made me ham and eggs. Then Franz Ramerstorfer took me to a “typical Viennese café” for coffee and Sacher Torte. This is Franz.

Franz is the Porter Novelli network’s “Digital Ambassador” in Austria, and leader of the Digital Taskforce out there, so this sets a new standard for Ambassador behaviour. I do hope the other ambassadors take notice. Thank you Franz and everyone at IKP for a great opportunity, and a great time!

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?

I believe that — like Caesar’s wife — those who work in the public relations industry must be above suspicion when it comes to all online engagement (whether personal or professional.) Later on in this post, you’ll see how I’m hoping to use our social media policy to moderate our behaviour as a company, while freeing up our colleagues to experiment with social media. But I’m not expressing it well. What should I do?

Last summer I shared a draft of the Porter Novelli Social Media Policy that I’d been working on.

It’s one of those documents that some like and some don’t. A few people, for example, think that it’s too restrictive.

The sticking point for most people seems to be the bit that says (under 2.3.3):

Your profile must include an explicit statement that you work for Porter Novelli. Include the following minimum information: “I work for Porter Novelli, a global public relations company.”

For a couple of reasons, this item has popped up again. A few weeks ago, I tweeted that Porter Novelli people should disclose their full name and company affiliation in their Twitter bios, and referred to a post-and-comments on this blog that went some of the way to explaining why this should be. This tweet was picked up by a few people, some of whom commented. Willem (@hippowill, Ice cream for everyone!!) was probably the most eloquent, saying (among other things):

I’m not looking for work, but if I do I’m not interested in applying for Porter Novelli or any other agency that would feel the need to require my agreement to online guidelines, telling me how to talk, write and represent myself – and not the agency I work for – online.

So I’ve been meaning to get back to him, if nothing else. I feel that either I haven’t explained our policy properly, or he doesn’t get it — which amounts to the same thing. I don’t mind being wrong, but I do mind being misinterpreted. This stuff is important!

Yesterday, I had a brief conversation with some of our graduate prospects — young bright people who are looking to work for us. And it turned out that one of them, Anna Svensson (@svanna) had already written a post about it, asking Does your future employer have the right to control your online interaction?

In her response, Anna points out that (while she still feels that we’re “trying to control [our] employees a bit too much”) what we’re actually attempting to do is more “a form of issues management” (exactly!) It’s a good post, but it’s one of those that’s worth reading for the comment stream. I’d recommend you take a read.

But here, I think, is the big question:

Should a PR agency’s social media policy be different?

Different, I mean, from other companies’ policies? You see, I’d argue “Yes, they should.” I’m basing this on a lot of previous material. Wikipedia’s Conflict of Interest guidelines, for example, explicitly state that public relations is a “special case”:

Editing in the interests of public relations is particularly frowned upon. This includes, but is not limited to, edits made by public relations departments of corporations or governmental entities; or of other public or private for-profit or not-for-profit organizations; or by professional editors paid to edit a Wikipedia article with the sole intent of improving that organization’s image.

The italics are my own. Public relations (and social media relations) people are – I think – likely to be more distrusted than usual. Our errors will be held up to ridicule by our customers, and by our peers, and will live forever in the popular schadenfreude, achieving the mythical status of the fake blogging fiascos of 2007, or poor bloody Kryptonite/Bic Biro events of 2004 that still turn up in presentations and training workshops.

We’re also under more pressure to make mistakes. Between us, PR professionals around the world represent hundreds of thousands of clients, and several million campaigns every year. As the pressure increases in every region to take these campaigns online, mistakes will be made.

While I was writing this policy, I came across lots of policies from other organizations. Most of these were old-school “blogging policies” (Forrester’s Charlene Li posted a list ofBlogging Policy Examples back in 2004) and there’s a list at the NewPR Wiki.

We wanted to do something a bit different. As I state in the policy preamble, we wanted it to cover “Anything you do online where you share information that might affect your colleagues or clients.”

I’d done a bit of quick-and-dirty internal research when I joined Porter Novelli. At the time (and even today) the great majority of our colleagues weren’t bloggers. As a result, any “blogging policy” would be irrelevant to them. And yet, at the same time, a majority of our colleagues were on sites like Facebook, LinkedIn, and Bebo, with some (mostly dormant) accounts on other social networking sites like Orkut, ASmallWorld, Hyves and the like depending on where they were coming from. A smaller number — while having no blog of their own — had commented on a blog or online news story, or posted in forums at least once in the past three months. Some of them were sharing photographs over services like Flickr, and (thankfully) a very few had — according to WikiScanner — anonymously edited Wikipedia (and, with one exception, always for non-client-related interests). Almost all had voted on something — even if it were only a poll — in the past quarter.

Some of these engagements were on behalf of clients, but the great majority were “personal business” — or as Willem might put it, representing themselves – and not the agency or clients for whom they worked.

The guiding principles for the policy

We were trying to keep things as simple as possible.

I rather like Comcast’s policy as quoted by Rohit Bhargava in his post Comcast’s Actual Social Media Policy No One Knew About:

Their official point of view is that their employees are allowed to participate authentically, as long as they disclose their affiliations, don’t divulge secret or proprietary information and don’t act as though they are an official spokesperson or allowed to speak on behalf of the brand.

That’s a lot better, I think than the often misquoted Microsoft “Be Smart” (taken out of context from a post from Robert Scoble” and a couple of often-quoted soundbites along the lines of “Our corporate policy is, be smart. We don’t talk about things we don’t know about.”)

Only the most arrogant would believe that “be smart” is suitable advice to include in a policy — instead it was a glimpse at the philosophy that underpinned the blogging policy that Microsoft were working on at the time. Scoble explicitly agreed with what Yahoo!’s Jeremy Zawodny says:

The only advice I have … is this: please make sure it’s abundantly clear what the rules are. You’re getting to be a big company. Don’t rely on unwritten rules or company tradition/culture to do the job.

So I was trying to keep it simple and flexible. Hence the guiding principles:

1. The web is not anonymous. Assume that everything you write can be traced back to the company, if not you personally.
2. There is no longer a clear boundary between your personal life and your work life.
3. Do not lie or withhold the truth.
4. The web contains a permanent record of our mistakes. But do not try to change things retrospectively.

Furthermore, I borrowed a philosophy from someone much wiser and smarter than I (and who was more fitted to our corporate culture than — say — Microsoft’s), Cluetrain Manifesto co-author David Weinberger who says:

All I can promise is that I will be honest with you and never write something I don’t believe in because someone is paying me as part of a relationship you don’t know about. Put differently: All I’ll hide are the irrelevancies.

So what’s the thinking behind Paragraph 2.3.3 then?

Well — there are several.

1. We’re proud of the people we hire, and we hope they’re proud to work for us

One of the most satisfying ways we recruit is through WOM recommendation from our colleagues, who have let their friends how much they enjoy working with us.

Because we think that our people are the best advertisement for who we are and what we do, we’d like to see them promoting their personal brands as much as possible. We actively encourage people to begin blogging, set up networks on LinkedIn, get on Flickr, Twitter, and the like. We don’t actively monitor these accounts, but do

2. It prevents us from forgetting that there’s no “private” anymore

I think that a good PR person is someone who manages their relationships well; who can tread the fine line between doing good work for their clients without abusing or exploiting their relationships. Who recognizes the value of their personal network, and their personal brand.

When I’m doing background research on someone I’m meeting, I’ll check Google, LinkedIn, Facebook and Twitter. Who are they? Where have they worked? Who do we know in common?

Have you heard the story about photos of Bono and “bikini-clad babes” turning up on Facebook? Have you every searched for Carpphone Warehouse on Flickr?

PR people (who work with them on a daily basis) are already aware that these tools are also a great tool for journalists. So only someone very naive should think that there’s a divide that people will respect (“Oh — I won’t look at their Twitter or Facebook accounts because that’s personal, and I’m only interested them in a business context”)

By encouraging our colleagues to label their accounts with their place of work, we are also encouraging them to be aware that (even in their private lives) they may be seen to represent us.

3. It prevents us from accidentally forgetting to disclose

OK — everyone should disclose where appropriate. We know that. But in the heat of the moment, it’s easy to forget. It’s particularly easy to forget when you have only 140 characters to express yourself “I work for Porter Novelli, a public relations company that represents brand x” will take up more than 50% of your available space.

4. It prevents us from “accidentally” “forgetting” to disclose

Imagine that sentence being read out with heavy-handed sarcastic finger quotes.

There are all sorts of schoolboy errors that we won’t be tempted to make if everyone who works for us is clearly labelled “Porter Novelli.”

Working in the nineties at media planning and buying agencies and creative agencies leaves me with an abiding memory of being asked to “click on any of our banners that you see while you’re surfing.” These days, thank God, technology and good auditing has put paid to this kind of abuse.

This kind of astroturfing (the term we use for faking grass-roots support) is the kind of behaviour we have to prevent. Leaving comments on forums and blogs, voting on polls, ’seeding’ UGC campaigns with content or sending apparently spontaneous branded ‘consumer’ messages via Twitter or Facebook is exactly the kind of thing that junior staffers will be asked to do by people who don’t get it. The fact that all our staffers are marked with the equivalent of a digital watermark prevents people from us as a company asking them to misuse their personal accounts.

I talked above about “personal networks” and “personal brands” — it’s essential that we as a company don’t ask people to exploit those; we want to hire people who have good networks. We want to help our colleagues develop those networks and brands. But while they work with us, we want them to use them on behalf of our clients. You can see how easy it would be unthinkingly to ask them to abuse them. By asking our colleagues to put the name of our employer on their accounts, I think we take a step towards preventing that.

This is a complicated idea — but one I hope that I’ve now explained better.

5. It prevents us from accidentally astroturfing again

Remember, Porter Novelli is a global organization. Different territories are at different stages of their digital market development. This is both an advantage (we can better forecast and plan for what future developments will look like in those markets) and a disadvantage (we may be condemned to repeat mistakes we — or our competitors — have made in more developed markets.)

Does this make it clearer?

To those, like Willem, who think that we’re being too strict I’d ask — does this make more sense? Do you still believe that there is “public and private?” Do you think that we’re simply doing this to advertise ourselves and control our employees, or do you think that we are doing it (as I suggested) to moderate our behaviour as a company, and freeing up our colleagues to experiment with social media?

What can I do to improve this? Now you know what we’re trying to do, all suggestions will really be welcomed.

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.

1. 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?
2. 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.”

3. 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.”

A recent post about some Pareto analysis of the Porter Novelli Twitter sample , “Porter Novelli Twitter folk – the 80/20 rule”, stirred up a little bit of interest on Twitter — and made me think again about what I’m doing and why. Partly because those conversations were off-blog (and I’d like to capture the answers I gave somewhere more permanent) and partly because I’ve now had time to think of better answers I thought I’d set them down here.

First, a little background. This Q&A is the sixth post in an impromptu series about the Twitter people where I work (Porter Novelli, the international public relations agency.) By now you might think that I’d be tired of this stuff, but you’d have another think coming. Here’s a quick list to bring you up to date.

1. Map of Porter Novelli people on Twitter on 17th Jan 2008
2. Map of Porter Novelli people on Twitter on 20th Jan 2008
3. Introducing the Porter Novelli magic Twitter friend maker (beta)
4. Porter Novelli Twitter folk ranked by number of followers
5. Porter Novelli Twitter folk – the 80/20 rule

Looking at this, you might also think I clearly had nothing better to do than analyze Porter Novelli people and their Twittering ways. In fact, as an experimental data set, I couldn’t really ask for anything much better. It’s sufficiently large (more than 200 people), international (I’ve counted more than 10 countries — and I’m sure there are more), and I have some real-world access to all of the people in the sample, which means I can compare my findings with some hard data.

That said, the experiment is more about learning about how we can analyze Twitter networks — about discovering how representative they are as a word-of-mouth (WOM) channel for example, and what they can tell us about other kinds of social network, or about finding new ways to analyze such data sets — than it is about answering any specific questions. So I’ve not got any carefully mapped-out research plan. Instead I follow paths that strike me as interesting, or possible, or that are suggested to me by friends and readers.

Question 1

I’ve posted this exchange as a slideshow so you can sort of follow along. Twitter updates are rather telegraphic (it’s the 140 character limit) so that’s another reason to take the time to answer the question more fully here.

Caroline (@lemondrizzle) is a Porter Novelli colleague based in London. She wanted to know what purpose of de-duping the follower list serves. The first answer is that it gives us a clearer idea of the sample set of Twitterers’ reach. Here’s what the unduped list looks like:

As I said in an earlier post, there must be many, many duplicated connections here.

When I de-duped the network, it looked more like this:

If we count people more than once it gives us an inaccurate picture of the potential impact of the network. Looking at the Alice/Bob/Carol example (I changed “Adam” to “Alice” after Caroline accused me of sexism) you’ll see there are two ways to count the followers.

If we include the duplicate entries, then the three have an apparent combined reach of 18 people. Once we de-dupe, they have a combined reach of 10. The same goes for the Porter Novelli Twitter network (only more so): once we dedupe that, it decreases from an apparent combined reach of around 21K users to a combined reach of around 6K people.

So were we able to mobilize everyone on our Twitter list in another campaign like Porter Novelli CMO Marian Salzman’s #pnobama exercise from last month, we’d reach around 6K people.

Of course, it’ll be impossible to mobilize everyone. By ordering the sample from most to fewest followers and de-duping, we could now identify our key targets for the activity and instead focus our attention on them.

Costs and Benefits

Furthermore we have a good understanding of the costs and benefits of this strategy.

Assume that we are dealing with a new Twitter network and not our own internal network. Assume further there is a “unit cost” of engaging with each new Twitter person in the network of one whojamaflip (where a whojamaflip might be a financial cost, or the amount of time and effort it takes to read their blog and previous tweets, work out who you know in common, prepare and deliver your pitch etc.)

Knowing that the top 20% or so of the group (at a cost of 40 whojamaflips) will reach 80% or so of all the followers — around 4.8K opportunities-to-see (OTS) at a cost-per-thousand (CPM) of 8⅓ whojamaflips — tells us a lot about how and where we should focus our efforts, and about the incremental benefit of reaching the remainder of the group — 1.2K OTS at a whopping and unjustifiable CPM of 133⅓ whojamaflips.

Do we really reach 4.8K people?

Of course not. For one thing, not every follower is “real”, and for another we can’t guarantee a view. One of my followers, for example, is Barack Obama. If I thought he were hanging on my every tweet, I’d be too scared to commit words to screen.

Instead we should see followers as opportunities-to-see (or “OTS”) rather than views or eyeballs.

Are numbers all that matter?

No, of course not. I tend to work on a simple model of “influence” that looks at 3 factors:

1. Popularity/Reach — the number of people whom an individual influencer can affect – generally a ’size of audience’ figure
2. Authority — ‘people who talk about subject x are most likely to mention these influencers’
3. Proximity — probability of being present at or involved or consulted in a given decision.

But even these won’t give you the whole picture, there are lots of other factors (things like “trust”, say) which don’t completely fit into this model. And — as people like Victoria have pointed out on previous posts — I make no judgment on things like how compelling a message or product we’re selling.

I think it’s a matter of perspective. Just like there are things that make an effective virus (things like a short incubation period, long infectious period and resistance to treatment, say) there must be things that make an effective message. Lots of people I know are (or have been) working on this. Indeed, I maintain a keen interest myself — I just don’t have much to share.

What do you look at, then?

Instead, I find myself looking at the channels, the vectors of transmission. To continue the virus metaphor; however virulent a virus may be, it makes little difference if (like smallpox) it is stuck in a few laboratory freezers and can’t get out.

What’s that about clumpiness and bridge nodes, then?

When we map networks of people we generally find that they are “clumpy” — what I mean is we can see many tightly knit groups of people who are linked to the other clusters by a few thin threads.

Take your own Facebook friends as an example. There’s a strong probability (depending on factors like your age group) that there will be around three or four clusters; most probably colleagues at your present job, university friends, and old school friends. Let’s say you share some news with these close-knit groups via Facebook. What incentive do they have to share the information on? There’s a very strong likelihood that they share many of the same friends and colleagues with you — the natural assumption must be that everyone who matters is already aware of the news you’ve shared. The last thing they want to do is tell everyone what you’ve already told them. Where’s the network utility in that?

What this means is that news is actually most likely to be repeated by people on the very edge of that group; people who are (from their position) less likely to think of that group as the only audience. These are the people who share stories; what — along with lots of other people in this area — we’re currently calling “bridge nodes.” Caroline doesn’t like me calling them bridge nodes, though, so we may need to address this. Otherwise she’ll steal my pencils.

Question 2

@Amber1230 asks a different kind of question, and one that’s a bit harder to answer.

As it happens, second-degree networks can (in fact) be factored into our calculations. I’ve done quite a lot of stuff with second-degree networks in the past. Take a look, for example, at this map I made of my Facebook connections and their connections back in 2007.

Sure, the maths becomes a little more complicated. If you really want to know, we start talking about things like “eigenvector centrality” rather than “degree centrality”. Eigenvector centrality says (more or less) “it’s not who you know, it’s who they know.” A short paper by Steve Borgatti called Centrality and AIDS has this description of the distinction:

In the context of HIV transmission, we can see that all else being equal, a person A with one sex partner has a better chance of escaping the infection than a person B with many. But if that one sex partner that A has is having sex with most of the network, A’s chances of getting infected are nearly as good as if she were having sex with all those others herself.

So far, I think this is exactly what @Amber1230 is saying. The problem is one of tense; I’m trying to predict stuff, not describe what has already happened. We know that everyone in someone’s first-degree network will have an opportunity to see the initial message. But the only ways that someone in the second-degree network might see it is if they are already in the first-degree network, or if one of the first-degree people retweets it (or does something off-network.) The retweets issue is actually rather difficult to solve (although some headway is being made by people like Dan Zarella and Joost de Valk among others.)

So for the moment, I’m trying to work with what I know — or what I can know.

Last weekend I posted a chart of Porter Novelli Twitter folk and their followers. If you read it, you’ll recall that I was dissatisfied by what it implied about the collective reach of Porter Novelli twitterers.
Well, thanks to a long-ish train journey to Bolton and back, I was able to fudge a little perl script together to look through the data to find and remove everything other than the first instance of a follower. Let’s make that a little clearer. Let’s say that we’re looking at three Twitter people, Alice, Bob, and Carol. The first thing to do is to see who follows them:

Now we need to rank them in order of “who has the most followers” (also known as “popularity” as it happens). Here I’ve done that from left to right. Bob has the most followers and Carol the fewest.

And finally we go through from left to right removing all followers who have already shown up on someone else’s list.

Bob, being at the top of the list gets to keep all his followers which may seem unfair. But it’s not unfair if the question we’re trying to answer is “how do I reach as many people as possible by speaking to as few people as possible?” That is, I’m looking for reach (marketing people often express themselves in terms of “reach” — or the number of people who are exposed to a message — and “frequency” — or the number of times the average person is exposed to that message.)

Looking at the example above, we can see that Alice really delivers an incremental benefit of two new people, and Carol only reaches one new person. That gives us a much better idea of how valuable the most popular person (Bob) really is.

Applying this to the Porter Novelli data set

Clearly it would be extraordinarily boring to perform the process described above for the 205 people in the Porter Novelli data set that I want to analyse. But the analysis script that I wrote (with plenty of help from the perl monks) goes through exactly these steps. It’s a pretty straightforward job, ranking and deduping. Here’s what we get.

This makes much more sense than the last run. According to the Pareto principle, roughly 80% of the effects should come from 20% of the causes. Here we see that 20% of the Porter Novelli Twitter users (marked in black) account for slightly more than 80% of the reach (marked in red.) It’s pretty much a text-book example. Things are as they should be, I suppose.

More to the point, we can now assign appropriate value to coverage at the head of the graph. This is of great value when thinking about our media planning and engagement

By the way — if you’d like a copy of either the Twitter follower API query engine (it’s a well-behaved command-line thing that was developed by the excellent Joachim Larsen) or the slightly shonky perl script that I wrote on the train, you have only to ask: I’ll be pleased to share. Send me a tweet at @mediaczar and I’ll send you the scripts.

Yesterday I did a little work with the TwitterCounter API. Today I’ve gone a little further and (purely as an experiment) ranked a list of Twitter people in Porter Novelli by the number of their followers.

What happens if we chart this? Here’s a kind of Pareto chart showing users ranked in order of followers and the total reach that we get at each stage.

If you’ve seen this kind of thing before, it looks wrong, doesn’t it? That red curve should be steeper at the beginning and have longer flatter asymptote. If you’ve ever heard of the 80/20 rule this is one of the graphs that describes it. Normally the head of the graph (the first 20% of the x-axis) controls around 80% of the value while the tail (the remaining 80% of the x-axis) controls around 20% of the value. If you’ve ever heard about the long tail, it’s this tail that Chris Anderson et al. are talking about.

What’s wrong with the data?

It’s not so much the data as what I’ve not done with it. There must be many, many duplicated connections here. So now I need to write something that will go through the followers of all the Porter Novelli Twitter usernames in ranked order, and only count unique (or unduplicated) followers.

I’m hoping that when I re-do the chart, it will look something more like this:

A couple of days ago, I posted a map of all the Porter Novelli people we knew of who are tweeting. The list keeps getting bigger: at today’s count, there are 212 known Twitter people.

At the moment, I manage three Twitter accounts (thanks mostly to the excellent Twhirl Twitter client that lets me log in simultaneously to as many accounts as I like. Two of those accounts are Porter Novelli-related, so it was essential that I follow everyone. Of course, I could simply set up an auto-follow using something like Tweetlater , but that wasn’t going to work if people didn’t know about and follow those accounts in the first place.

So I pulled together a little seven-line perl script that would do this for me (included at the end of this post.) This was always going to be a personal tool, but when I looked at the map of current Porter Novelli Twitter people, it became clear that:

1. There are lots of new people in our company joining Twitter
2. They don’t have many friends yet. Twitter isn’t much fun when you don’t have friends.
3. If we could come up with some way for them to make friends with other people in our network quickly, then we’d have a more robust, more useful network

For various reasons it was hard for me to get the perl script working on this site as a tool for everyone. One of those reasons is that I don’t build very secure programmes, and if anyone entered their name and password on my site, they would be stored in my log files. While this would open fascinating opportunities for pranking, it would obviously compromise my reputation for high ethical standards should it ever get out.

So I commissioned someone to build a simple Twitter befriender. It’s rather shaky at the moment (the feedback is less than user-friendly for example) but here’s how it works.

1. You enter your Twitter username and password. They will remain private (only Twitter will see them)
2. The magic Twitter friend maker looks at the list we’re maintaining on Google Docs and tries to follow everyone on that list
3. It spits out a list of errors (people you may already be following or who have protected their feeds, for example.)

That’s it. Suddenly you’re following up to 200 new people. More than 75 people have used it already, and the Porter Novelli network is becoming stronger by the minute!

Feel free to have a play with the magic Twitter friend maker, but do read the caveats below.

Caveats

It only follows known Porter Novelli people on Twitter. You may not want to do this, although I cannot imagine why not.

Not everyone in Porter Novelli speak English all the time. We are an international agency after all and you have to take the rough with the smooth.

This is in beta. It may fail. If so, please leave a comment here, or send a tweet to @mediaczar. Please check your friend numbers before and after using the magic Twitter friend maker.

If you don’t have many followers already, the sudden rush of following activity may make you look a bit keen; this might affect your Twitter Grade. If you work for Porter Novelli, then this should all come out in the wash, somehow.

If you don’t already have lots of friends, the sudden increase may confuse you at first. But be reassured: using Twitter well kinda requires you to follow and be followed by lots of people. I recommend getting hold of a Twitter client like Twhirl or Tweetdeck and learning how to use it.

That should be it, I think. Updates will be added to this post.

Perl script

[code lang="perl"]#!/usr/bin/perl

use Net::Twitter;
my $twit = Net::Twitter->new(username=>"your username", password=>"password" );
my @usernames = qw(insert twitter usernames here separated by spaces);

foreach $user(@usernames) {
print "$user\n";
$twit->create_friend($user);
}

$twit->update("Just finished following all my Porter Novelli colleagues");[/code]

It uses the Net::Twitter perl module written by Chris Thompson (and is a profligate waste of a great module, BTW.)

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.)

This is a map of the 156 Twitter people that I knew about this morning (there are still others coming in). The size of the blob is an indicator of how many of that person’s peers follow them on Twitter, and the colour (running from white at the “hottest” through orange and red to blue at the “coldest”) indicates how structurally important that person is. For more on this, see yesterday’s post showing the Twitter map on 17th Jan 2008.

More cohesion

Here’s what happened when I remove the ten main connectors from the old map. It falls apart.

17th Jan map (67 nodes)	10 highest betweenness nodes removed

And here’s what happens now.

20th Jan map (155 nodes)	10 highest betweenness nodes removed

You’ll see that much less damage is done now; the network is much more decentralized, thanks to a concerted effort by Marian et al. to promote cross-linking behaviours. Of course, we’re now removing around 6% of the network compared to 14%, but if the network were still as unlinked as it used to be, that would make no difference. This is on the whole, a more cohesive network.

I say “on the whole” because of the isolates (unlinked nodes) that are displayed at the top left. These are people who are new to twitter, and who haven’t yet made any friends or attracted any followers. This is one of the problems we’re trying to address; I’m considering building a “follower bot” that will help new Porter Novelli joiners (and anyone else who cares to do so) automatically follow all the other Porter Novelli twitterers (should I get over my distaste for the word “tweeple”?)

Weaknesses

As Tikva and others have pointed out, simple linking isn’t enough to really rank people in this network. You’d want to look at other quantitative metrics. Recency, frequency and tenure spring to mind, of course; but I’d also want to see things like who (in the network) is most often addressed or quoted using the “@<username>” convention. We’ve been building an “eavesdropping” bot to help us get a grasp of that sort of thing, but we’re still not there (the code works, but I can’t get it to run on my server yet…)

On the qualitative side, we’re also missing important things like “how much one person likes, is indifferent, or dislikes another” (there has to be a better way of expressing that.) I don’t really do qual measurements at present; I want to be able to get a whole load of stuff out of the way before I even begin to deal with tricky stuff like that. Is this an Aspergers thing, do you think, or am I just being male?

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

Simply asking people doesn’t really work. Marian’s scheme gives us a shared sense of purpose, which is one of the criteria for creating a strong community. It’s a much better plan all round.

But — of course — I want to see whether I can track how that works in practice. What do the before and after photos of a strong community look like?

The map above is the “before” map. You can see that there’s some nice heavy clumping down in the bottom of the chart, but a lot of pendants towards the top of the graph — people who are held into the main network mainly because of @robmctree. If he were to leave the network, you can see that some of them would float away to become like the eight other unconnected nodes at the top left.

That’s why his node shows slightly “hotter” (we rank the nodes according to a colour scale from deep red at the coolest to white at the hottest.) The hotter the node, the higher its “betweenness centrality” (basically a measure of its structural significance – if you remove the nodes with high betweenness centrality, the network tends to fly apart faster than if you remove the others.)

@mediaczar (that’s me) is big and white. The size indicates how many other people in the network follow that user (me.) Normally the big nodes in a network have all the betweenness centrality.

What’s interesting is using this technique to identify those (like @robmctree, @noahbanning, @volapuk, @angie_s and @amytokes) who have relatively low link popularity but high structural significance.

To give an idea of how significant these high betweenness centrality individuals are to the network, here’s are two maps: the original map, and a map with the ten highest scoring individuals removed.

Before…

and after.

Like finding “top bloggers”, finding “top twitterers” is relatively easy. But approaching them is harder: there may be more demands on their time, for one thing. But if we can identify those who are less “popular” but who may still carry lots of weight within the network, we may be able to find softer targets for our comms activities.

On another note: this project would never have happened without @mariansalzman, @tikkers, or @zeenat58 who have been tireless on the internal email channels. This only goes to show that mistaking the channel for the network is an error into which we can too easily fall.