I write this post with some trepidation, because we have come up with a new list and lists I have learned are controversial. Some weeks ago Jonny Bentwood who runs tech analyst relations at Edelman’s London office and I were debating influence and how the Facebook phenomena has changed things. When people talked about on-line influence in the past they were often referring to bloggers and Technorati scores, though obviously influence was always more complicated than that. But now with the increasing mass adoption of Twitter and Facebook and favourites listings like Digg and Del.icio.us things have moved on. Bloggers Twitter and Facebookers Dig. Many of us are multi-platform users and so our online ‘footprint’ is much more dispersed.
So we thought we would have a bash at measuring it. Underlying this attempt is the presumption that a cumulative and comparative score can be assigned for an individual’s use of the various social media platforms that are available. That is no small presumption and the assigning of mechanical scores is a blunt instrument to say the least. How do you compare the influence of a Hugh MacLeod cartoon to a Robert Scoble tech review? Technorati say this about their methodology: “On the World Live Web, bloggers frequently link to and comment on other blogs, creating the type of immediate connection one would have in a conversation. Technorati tracks these links, and thus the relative relevance of blogs, photos, videos etc”. So putting numbers to these things and assuming a level of influence from them is not exactly new.
What we have tried to do is add some new ways of measuring influence via platforms like Twitter and Facebook to blog scores. This is definitely adding apples to oranges we admit. So for example, we are placing a score for Facebook depending on the number of friends someone has. For Twitter, it is the number of friends, followers and updates. And if that is not insulting enough, we are then coming to a comparative weighting of someone’s Facebook score against their Twitter and blogging score. And the most sinful step is of course the final one where we have added those scores together and come up with a total Social Media Index. Which is an A list or a league table by another name I suppose. But we are not claiming it is definitive (how can it be with as many value judgements as I just confessed too) and we’re not entirely sure if the thesis itself will stand up. What we hope to do by this is to contribute to the debate and (and if possible) come to a community view of how you look at this. Why? Well, for us it is part of our business and I make no apology about that. Measurement is central to what we do and social media is massively powerful and we need to understand it to do our jobs. Many people do not like this and for them there is no good way of describing this.
So stage one; we created a Top 30 bloggers list from CNET Blog 100, Times Top 50 Business Blogs, Power 150 Top Marketing Blogs, Friendly Ghost Top PR Blogs and Technobabble 2.0 Top Analyst Blogs. A familiar enough grouping, but if you look along the top line you will see the new platforms we intend to combine with this listing.
Top 30 Blog – SMI weighting: 100% blogs
| Name |  |
 |
 |
 |
 |
 |
 |
|
|
1 |
98 |
0 |
0 |
0 |
0 | 0 |
98 |
|
| 2 | Search Engine Watch | 98 |
0 |
0 |
0 |
0 | 0 | 98 |
| 3 | Boing Boing | 98 |
0 |
0 |
0 |
0 | 0 | 98 |
|
4 |
97 |
0 |
0 |
0 |
0 | 0 |
97 |
|
|
5 |
96 |
0 |
0 |
0 |
0 | 0 |
96 |
|
|
6 |
96 |
0 |
0 |
0 |
0 | 0 |
96 |
|
|
7 |
96 |
0 |
0 |
0 |
0 | 0 |
96 |
|
| 8 | John Battelle’s Searchblog | 96 |
0 |
0 |
0 |
0 | 0 | 96 |
| 9 | Techdirt | 96 |
0 |
0 |
0 |
0 | 0 | 96 |
| 10 | Pronet Advertising | 96 |
0 |
0 |
0 |
0 | 0 | 96 |
|
11 |
95 |
0 |
0 |
0 |
0 | 0 |
95 |
|
|
12 |
95 |
0 |
0 |
0 |
0 | 0 |
95 |
|
|
13 |
95 |
0 |
0 |
0 |
0 | 0 | 95 | |
| 14 | Copyblogger | 95 |
0 |
0 |
0 |
0 | 0 | 95 |
|
15 |
94 |
0 |
0 |
0 |
0 | 0 |
94 |
|
| 16 | SEOmoz Blog | 94 |
0 |
0 |
0 |
0 | 0 | 94 |
| 17 | Jonathan’s Blog | 94 |
0 |
0 |
0 |
0 | 0 | 94 |
| 18 | The Blog Herald | 94 |
0 |
0 |
0 |
0 | 0 | 94 |
| 19 | direct2dell.com | 93 |
0 |
0 |
0 |
0 | 0 | 93 |
| 20 | Romenesko | 93 |
0 |
0 |
0 |
0 | 0 | 93 |
| 21 | PaidContent.org | 92 |
0 |
0 |
0 |
0 | 0 | 92 |
| 22 | Secret Diary of Steve Jobs | 92 |
0 |
0 |
0 |
0 | 0 | 92 |
|
23 |
91 |
0 |
0 |
0 |
0 | 0 | 91 | |
|
24 |
91 |
0 |
0 |
0 |
0 | 0 |
91 |
|
| 25 | Seth Godin | 91 |
0 |
0 |
0 |
0 | 0 | 91 |
| 26 | Logic+Emotion | 91 |
0 |
0 |
0 |
0 | 0 | 91 |
| 27 | tompeters! | 91 |
0 |
0 |
0 |
0 | 0 | 91 |
| 28 | GrokDotCom | 91 |
0 |
0 |
0 |
0 | 0 | 91 |
|
29 |
89 |
0 |
0 |
0 |
0 | 0 |
89 |
|
| 30 | adfreak | 89 |
0 |
0 |
0 |
0 | 0 | 89 |
This next chart is the same 30 people, but now we have added individual scores for their use of non-blogging platforms and in the final column come to a total Social Media Index or score for them. Here’s how we did that:
Each person has been given a score out of 10 based upon 6 criteria:
- Blog – analysed Google Rank, inbound links, subscribers, alexa rank, content focus, frequency of updates, number of comments
- Multi-format – analysed Facebook – number of friends
- Mini-updates – analysed Twitter – number of friends, followers and updates
- Business cards – analysed LinkedIn – number of contacts
- Visual – analysed Flickr – number of photos uploaded from the person/s or about the person/s
- Favourites – analysed Digg, del.icio.us
Each score out of 10 was the given the following weighting across the categories : Blog – 30%; Multi-format – 20%; Mini-updates – 25%, Business cards – 7%, Visual – 3%; Favourites – 15% which created a total score for each category. The sum of each of these numbers created an individual’s Social Media Index. Clear as mud. And about as appetising for some I suspect, because the weighting system is massively subjective. I repeat, it is our first stab at it and we are interested in your take.
And these results are vaguely embarrassing for us too, because the conspiracy minded will have noticed that Edelman’s own Steve Rubel of Micropersuasion fame is (drum roll) number one in this (surprise, surprise) Edelman league table. And we know how well that will go down. But the fact is he is so prolific across all platforms it is what it is. Personally I think he needs to do some client work some time.
Top 30 Blogs – SMI tiered weighting
Weighting: Blog – 30%; Multi-format – 20%; Mini-updates – 25%, Business cards – 7%, Visual – 3%; Favourites – 15%
| Name | |
|
|
|
|
|
|
|
|
1 |
29 | 17 | 25 | 7 | 2 | 13 | 93 | |
| 2 | 29 | 20 | 22 | 0 | 3 | 13 | 87 | |
| 3 | 29 | 20 | 25 | 0 | 3 | 9 | 86 | |
|
4 |
29 | 20 | 13 | 7 | 3 | 13 | 85 | |
| 5 | 28 | 20 | 22 | 3 | 2 | 5 | 80 | |
| 6 | 29 | 16 | 25 | 4 | 2 | 4 | 79 | |
| 7 | 27 | 15 | 24 | 6 | 3 | 2 | 77 | |
| 8 | 27 | 16 | 14 | 0 | 3 | 12 | 72 | |
| 9 | 28 | 8 | 15 | 6 | 2 | 7 | 67 | |
| 10 | 27 | 5 | 19 | 4 | 1 | 8 | 64 | |
| 11 | 28 | 15 | 12 | 0 | 2 | 5 | 62 | |
| 12 | 29 | 17 | 0 | 7 | 3 | 5 | 61 | |
| 13 | 28 | 20 | 0 | 5 | 2 | 5 | 61 | |
| 14 | 28 | 13 | 3 | 0 | 0 | 8 | 53 | |
| 15 | 27 | 5 | 0 | 0 | 3 | 9 | 45 | |
| 16 | 29 | 0 | 0 | 0 | 3 | 11 | 42 | |
| 17 | SEOmoz Blog | 28 |
0 |
0 |
5 | 3 | 5 | 41 |
| 18 | Search Engine Watch | 29 |
0 |
0 |
0 |
0 | 9 | 38 |
| 19 | Boing Boing | 29 |
0 |
0 |
0 |
3 | 5 | 38 |
| 20 | Jonathan’s Blog | 28 | 1 |
0 |
0 |
2 | 4 | 36 |
| 21 | PaidContent.org | 27 |
0 |
0 |
0 |
3 | 4 | 34 |
| 22 | Secret Diary of Steve Jobs | 27 |
0 |
0 |
0 |
0 | 6 | 34 |
| 23 | adfreak | 27 |
0 |
0 |
0 |
0 | 6 | 32 |
| 24 | The Blog Herald | 28 |
0 |
0 |
0 |
0 | 3 | 31 |
| 25 | direct2dell.com | 28 |
0 |
0 |
0 |
0 | 3 | 31 |
| 26 | Pronet Advertising | 29 |
0 |
0 |
0 |
0 | 2 | 31 |
| 27 | Romenesko | 28 |
0 |
0 |
0 |
0 | 3 | 31 |
| 28 | Logic+Emotion | 27 |
0 |
0 |
0 |
1 | 2 | 30 |
| 29 | tompeters! | 27 |
0 |
0 |
0 |
0 | 3 | 30 |
| 30 | GrokDotCom | 27 |
0 |
0 |
0 |
0 | 3 | 30 |
But this list just orders in a new way, a list of top bloggers. We then looked wider a-field to try and come up with a more pure Social Media Index where we have added top scorers not restricted to the blogging top 30. Same methodology, just a wider catchment group. Yes and Steve is still number one.
Top 30 social media index
Weighting: Blog – 30%; Multi-format – 20%; Mini-updates – 25%, Business cards – 7%, Visual – 3%; Favourites – 15%
| Name | |
|
|
|
|
|
|
|
|
1 |
29 |
17 |
25 |
7 |
2 |
13 |
93 |
|
|
2 |
29 |
20 |
22 |
0 |
3 |
13 |
87 |
|
|
3 |
29 |
20 |
25 |
0 |
3 |
9 |
86 |
|
|
4 |
29 |
20 |
13 |
7 |
3 |
13 |
85 |
|
|
5 |
28 |
20 |
22 |
3 |
2 |
5 |
80 |
|
|
6 |
29 |
16 |
25 |
4 |
2 |
4 |
79 |
|
|
7 |
27 |
15 |
24 |
6 |
3 |
2 |
77 |
|
|
8 |
25 |
20 |
23 |
0 |
3 |
6 |
76 |
|
|
9 |
21 |
19 |
23 |
6 |
2 |
3 |
72 |
|
|
10 |
27 |
16 |
14 |
0 |
3 |
12 |
72 |
|
|
11 |
26 |
12 |
21 |
5 |
1 |
6 |
71 |
|
|
12 |
23 |
15 |
20 |
5 |
2 |
3 |
68 |
|
|
13 |
18 |
16 |
25 |
2 |
3 |
4 |
67 |
|
|
14 |
28 |
8 |
15 |
6 |
2 |
7 |
67 |
|
|
15 |
23 |
16 |
15 |
6 |
2 |
4 |
65 |
|
|
16 |
24 |
15 |
15 |
5 |
2 |
4 |
65 |
|
|
17 |
27 |
5 |
19 |
4 |
1 |
8 |
64 |
|
|
18 |
23 |
5 |
23 |
5 |
1 |
5 |
63 |
|
|
19 |
25 |
5 |
23 |
1 |
2 |
6 |
63 |
|
|
20 |
24 |
15 |
21 |
0 |
1 |
2 |
62 |
|
|
21 |
28 |
15 |
12 |
0 |
2 |
5 |
62 |
|
|
22 |
29 |
17 |
0 |
7 |
3 |
5 |
61 |
|
|
23 |
28 |
20 |
0 |
5 |
2 |
5 |
61 |
|
|
24 |
24 |
4 |
17 |
5 |
3 |
6 |
59 |
|
|
25 |
26 |
11 |
12 |
6 |
0 |
4 |
58 |
|
|
26 |
20 |
12 |
18 |
4 |
3 |
1 |
58 |
|
|
27 |
20 |
15 |
15 |
3 |
0 |
4 |
57 |
|
|
28 |
19 |
12 |
15 |
4 |
1 |
5 |
56 |
|
|
29 |
25 |
0 |
22 |
0 |
3 |
6 |
56 |
|
|
30 |
26 |
5 |
17 |
6 |
0 |
1 |
56 |
So what does this last list mean? The overwhelming majority of new entrants to this more ‘pure’ Social Media Index are individuals which is probably not surprising given that corporates or even collectives don’t really use Twitter or Facebook . . . people do. Obviously each platform has different primary functions and some are much more personal (Facebook) than others. But bloggers quite openly use Twitter and Facebook and MySpace to market their blog posts and many blogs these days have widgets cross marketing the individual’s Facebook or Twitter profiles. And the personal and the professional was a line blurred for many of us years ago.
There are of course many platforms that we did not include in this, like MySpace, Jaiku and Pownce and of course this list is very English-language centric and includes none of the local social sites which dominate in countries like Korea and Germany. We may well do this in draft two depending on what people think, but for now we thought we had enough in for the basis of this to be discussed.
Obviously Jonny Bentwood and myself will be delighted to get your feedback. If people think it is worth trying to come to some sort of wider community consensus on this we can look at putting that to a wiki or even hosting some sort of debate at a later date.
Methodology
a) Blogs
Google PageRank is a link analysis algorithm that interprets web links and assigns a numerical weighting to each site. High-quality sites receive a higher PageRank. The ranking uses the actual PageRank as part of its algorithm.
Bloglines displays the amount of subscribers each blog has to its feed(s). Subscriber ranges were determined and each range was assigned a number that was used as part of the algorithm.
Technorati ranking relates the authority of a particular blog (via the number of sites pointing to it). The more link sources referencing your blog, the higher the Technorati ranking. Similar to the Bloglines Subscribers value, and each range was assigned a number that was used as part of the algorithm.
Content/Frequency/Comments
Scores with strict criteria were assigned to content focus, frequency of posts and number of comments. The combined score was used as part of the algorithm.
Alexa ranks web pages based on usage of millions of people. It is a combined measure of page views and users (reach). As a first step, Alexa computes the reach and number of page views for all sites on the Web on a daily basis. The main Alexa traffic rank is based on the geometric mean of these two quantities averaged over time (so that the rank of a site reflects both the number of users who visit that site as well as the number of pages on the site viewed by those users). Ranks closer to 0 have been assigned a high number that was used as part of the algorithm.
b) Multi-Format
As a multi-format tool, Facebook was selected to identify a persons influence/popularity. Other formats such as MySpace could be used at a latter date. The number of friends was determined and each range was assigned a number that was used as part of the algorithm.
c) Mini-Updates
Twitter Friends and Followers Ranking
As a multi-format tool, Twitter was selected to identify a persons influence/popularity. Other formats such as Pownce could be used at a latter date. The number of friends and followers were combined to determine a total friends and followers score. Each range was assigned a number that was used as part of the algorithm.
Twitter Updates Ranking
The number of twitter updates was determined and each range was assigned a number which was combined with the friends and followers score to give a total that was used as part of the algorithm.
d) Business Cards
For Business Cards, LinkedIn was selected to identify a persons influence/popularity. Other formats such as Plaxo could be used at a latter date. The number of connections was determined and each range was assigned a number that was used as part of the algorithm.
e) Visual
For visual tools, Flickr was selected to identify a persons influence/popularity. Other formats such as YouTube could be used at a latter date. The number of pictures about uploaded about an individual or about that person was identified and assigned a number. Each range was assigned a number that was used as part of the algorithm.
f) Favourites
The number of Digg’s an individual has had was identified and assigned a number. Each range was assigned a number that was used as part of the algorithm.
The number of pages in an individuals own del.icio.us library was identified and assigned a number. Each range was assigned a number that was used as part of the algorithm.
Del.icio.us Others Library
The number of pages of an individuals own postings that have been saved in other users’ del.icio.us library was identified and assigned a number. Each range was assigned a number that was used as part of the algorithm.
Moving forward other tools such as Reddit will be included to make the scoring more complete.
g) Flexible weighting
Each specific social media outlet listed above was given a standard score out of 10. Using a flexible weighting scale it is possible to vary the importance of the different tools available and consequently establish different total scores of individuals web influence. For the table listed above the following weightings were used:
Blogs 30% Multi-Format (e.g. Facebook) 20% Mini-Updates (e.g. Twitter) 25% Business Cards (e.g. LinkedIn) 7% Visual (e.g. Flickr) 3% Favourites (e.g. Digg, del.icio.us) 15% The weighting scale listed above was created through discussions with several key new media gurus. I do not anticipate this weighting scale to be the final standard and welcome everyone’s views as to what this should be.
Future copies of the Social Media Index will allow you to assign your own subjective weightings to the index to establish your own score.
sixtysecondview.blog 
I’m curious about the Digg score…does the “number of Digg’s an individual has” refer to the number of times a person’s submitted links have been dugg, or to the number of items they’ve voted on themselves, or the number of items they’ve submitted to the service, regardless of whether or not they land on the front page? Or none of the above?
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Hi Jason
Regarding Digg, the numbers are calculated by analysing how often a particular domain has had it’s pages ‘digged’. (i.e. this applies to every page – not just the front page).
In addition, Digg works by only allowing one user to digg a specific page.
The Digg score does not include how many times a user has submitted a digg.
Hope this clarifies things for you.
Jonny
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I have to say, I’m extremely disappointed in this post, and the fact that so little research has apparently gone into this project to determine whether it would be even vaguely valid. If it shows anything, it’s that the people behind it really still understand very little about social media tools, other than how they benefit them directly. I find it so disappointing, because I work not only on the PR side of things, but also the tech end through running around 2 dozen sites of my own on top of my clients predominantly being webmasters and online entrepreneurs (several at the top of their fields, including online communities). Here are some of the fundamental faults with this idea (the same shared by pretty much every other ranking system in existence for blogs):
1. Facebook – Using Facebook doesn’t demonstrate influence in the slightest. Anyway can start an account, and add random users as friends. It doesn’t mean they actively use the account or exercise any influence over them. On top of it, Facebook isn’t valid for all niches by a long shot, and with Myspace cracking down heavily on auto-friend-adder bots, it leaves Facebook and the other social networks more open to the social media spammers (who can generate tens of thousands of friends quickly, but with no real interest in what they have to say). Facebook being more popular perhaps in Europe is fine, but that only makes it valid (but even that not really) if you’re talking about influence with a European audience, and nothing wider.
2. Twitter – Twitter’s really such a joke that I’m absolutely shocked to see it here. It’s actually discouraged quite aggressively in the blogging community, as a big contributer “blog clutter.”
3. Even the mention of Digg and Del.icio.us is amusing. The same goes for things like Technorati. If the PR community actually paid attention, they’d know that these once-useful tools are rendered worthless in gauging popularity with the overwhelming abuse that grows daily. You have paid Diggs, favorite and bookmark exchanges to improve rankings, etc. It’s sad, but it’s a reality in Internet marketing and SEO efforts, and it’s time to stop ignoring it.
4. Where are you pulling your inbound link count from?? Google, Yahoo!, and MSN can’t even come close to the same estimates (often by the thousands), so there’s no real authority source to pull this info from. Even if you went by Google’s standards because of their market share, you run into the issue that they choose to ignore and devalue certain backlinks for the purposes of their own ranking algorithms… which has nothing whatsoever to do with overall popularity and influence.
5. Google Pagerank – Obviously the PR community missed the Web memo that PageRank means almost nothing unless you’re selling backlinks on a website based on their ability to pass link juice (which Google actively discourages and is trying to weed out). It’s also incredibly easy to manipulate, and changes radically based on algorithm changes at Google’s whim… not with necessarily with changing influence. You also mentioned backlinks separately in your post. If you’re intending to count them both separately, you’re double-counting the same information, as incoming links are the driving factor behind Pagerank.
6. Content frequency tells you pretty much nothing, if you can’t vouch for content quality at the same time (and there really isn’t a way to do that… hence the issue with the entire ranking system really). Using it as a standard means that splogs have a better shot in that area than legitimate blogs.
7. Alexa – I’m utterly amazed that there’s still a living soul that gives any value to an Alexa rank. Again, it shows how out of touch the originators are with the tech side of the equation. Alexa rankings are the most easily manipulated ranking in existence, through simple URL redirects, autosurfing, and browsing your own pages. It’s reliance on the Alexa toolbar means most traffic to a site isn’t even factored into the equation, which is why Alexa has a tendency to be dominated by sites aimed at tech geeks and early adopter-types.
8. LinkedIn – If you’re only evaluating business-oriented blogs, this might not completely suck, but it’s also not used widely enough yet (even assuming no manipulation, which is highly unlikely) to justify using it as a yardstick to measure influence.
The most fundamental problem that you’re missing with this social media index is that you’re making a faulty correlation between social media and a blog’s influence, while simultaneously ignoring other extremely strong factors.
Frankly, a blog’s influence depends entirely on knowing one’s target market and what tools are likely to influence them. Your system can’t account for the fact that these tools simply don’t work all markets in even close to the same way.
You’re also ignoring things like paid advertising (increasingly popular for driving targeted traffic to content-oriented sites like blogs). You ignore it because it doesn’t fall within your limited scope of social media. Yet it leads to more targeted traffic than a lot of these other sources, and therefore traffic more easily influenced by the blogger. It’s just one example of why you can’t equate a social media “score” to the influence a blog has.
You also ignore a variety of other factors that can equate to influence, such as media coverage of the blog, interviews done with the blogger, the blogger’s level of communication in non-typical social media environments like forums and comments on related blogs, etc. It all matters. But it’s not all something you can measure in a hands-off, automatic way, with info plugged into an equation. I don’t blame you for not including these things, because of the sheer work that would be involved. But then please don’t claim to be offering an even slightly honest listing of blogs by their level of influence.
All you really ended up with is yet another list touting the same “top” bloggers (some deserving; some not so much), which in turn will simply drive even more traffic and exposure their way, showing quite directly that influence can be decided by enormously more than social media.
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Glad to see that there is at least one other person in the world that can see this for what it is… nice work Jennifer…
This is not a rank of influence it is a rank of how often certain individuals open their mouths. There is no quality score what-so-ever, there are no indicators as to what audience this stuff is reaching (if any) and the weighting is an absolute joke. Did any thought go into it or were numbers just randomly plucked from thin air? This is just an indicator of how much noise these people are introducing to an already overly congested media with no indication as to what effect this noise is having.
The appalling lack of understanding as to how social media works that is demonstrated here is shocking. Aside from the fact that having 4400+ friends on facebook is just ridiculous (it is about two-way interaction, does anyone in the world have the time to interact with over four thousand people?), the egotistical use of the word ‘followers’ instead of friends further demonstrates the misuse of the medium… these guys are trying to turn Facebook into blogs. They clearly do not get how New Media and Social Media are being used by the general public and instead are using the excuse of bringing much needed measurement and understanding of the internets impact as part of the marketing mix to blow their own trumpets within their existing sphere of influence.
I would be more angry about this sorry excuse of a methodology potentially damaging the industry of reputation management but thankfully it is so poor that the vast majority of people will see it for what it is, a cheap publicity stunt by Edelman.
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Jennifer and Nicolas I am sorry we disappointed. You make many good points, some of which have been made by other commentators and which we are taking on-board. The key one of these I think was my use of the word “influence” when as you rightly point out much of what we were ‘measuring’ was reach. However, you both talk as if we put this up as some sort of definitive view rather than a “first bash”. In fact, I don’t think we could have been less definitive and more apologetic for the approach then we were in my post. We talk about “presumption” and adding “apples and oranges” and the “insult” of our method of comparative weighting. And we expressly said this was not about the list produced but about how we talk about multi-platform use. We even said “we are not sure this will stand up”. And we expressly asked for input and feedback (and again thanks for yours) so I hope this makes you a little less “angry”.
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It’s not so much a matter of being “angry” as being shocked that people in the PR industry, especially at Edelman’s level, are this far behind in understanding what these tools really are, how they really work, and how they’re really being used. There seems to be this assumption that these tools are actually being used as they may have been originally intended by their creators, but that simply isn’t the case. Unless you’re working down in the trenches with the webmasters and online entrepreneurs creating and using these kinds of platforms, and not just jumping on them based on their own buzz after the masses are already ahead of the game, chances are that you’re clueless (not you personally; speaking generally regarding members of this industry).
The post was definitely extremely disappointing, because obviously thought went into it, and people thought they were doing it “right,” while missing a heck of a lot. The comments were / are definitely meant to be constructive, and perhaps a bit of a reality check. Support for something like this doesn’t necessarily make it a good idea… it does however demonstrate a more widespread naivety that’s a bit disturbing.
Hopefully Edelman takes the issues to heart and either comes up with a more legitimate ranking model or drops it, so as not to become yet another false source of rankings in the blogosphere seeming to say only that “bigger is better.” At least it would all be worthwhile if at least a few readers here listen to the comments from their colleagues and take this as a stepping stone to finally educating themselves a bit more on the world of social media… and not just from the already completely “lost” PR community.
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Jennifer,
We are taking the comments to heart and will be having another go in some form soon, though I personally believe this will be more in the area of getting a view of reach or footprint rather than ‘influence’ which I think is too big a claim for pretty much any mechanical method (though Peter Hirshberg of Technorati is pretty compelling on why their system can do this). And ultimately of course, the best system is going to be a massively blunt instrument and out of date as soon as published (are we not always in beta?). The “angry” quote was referring to Nicholas the subsequent comment to yours by the way.
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This might be helpful for you guys, as you write a number of emails that might want some flavor? Ever want an email that would self-destruct or send an email you don’t want someone to be able to print? Take back that email you wrote to your boss at 2AM
Check out http://www.BigString.com
It is a new free webmail program. When you send mail from your BigString account, you are protected. BigString is like an automatic shredder for your email. You can self-destruct or change an email that’s already been sent or read.
Have a great day!
Michael
michaelf@bigstring.com
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We’re still a new site, but I dunno, we’ve felt kind of influential.
Why don’t you skip all the bizarre metrics? You’re a PR company. Just use your own internal data of what impact mentions on the blogs you monitor have.
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Interesting that this kind of debate is going on in the broader corporate world but I would have to agree with a few of the skeptics that is all about “noise” (reach to put it kindly) rather than “true influence”. The very nature of social media means that an influential network is not determined by the number of friend links – as is very easy to end up with thousands of friends and spammer adder-ons – so this metric is fundamentally flawed. I would be interested in an influence metric which would assess the number of comments on a site (even if these are inflated by the blog owner replying back to posts or trackbacks). I recently posted about this on my blog because for example MIT are doing some really interesting work uwing a tool to measure the true influence of social media site visitors – which if combined with feed subscriptions, number of comments on blog and technorati rankings (although again technorati is also fundamentally flawed – ie links on one’s own site can influence one own’s rankings). At least this is provoking a broad debate though 🙂
My thoughts are here in more detail if anyone is interested:
http://marianina.com/blog/2007/07/02/social-networking-analysis-meets-web-analytics-meets-marketing-effectiveness/
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