Michael Arrington had the same change-of-mind about Klout that I recently did. Although I didn’t turn around and invest (although maybe I should).
- Bonnie Stewart, Klout is bad for your soul
Stewart digs into Klout with real feeling, taking a highly detailed look at what social media ratings and rankings do to us, and it ain’t good.
The new elite?
Bal Harbour Shops threw a party and only people with Klout influence scores of 40 or higher were eligible to come.
A bit general, since I have a Klout score above 40 (67 at the time of this post), but I am totally uninfluential in fashion (or I think I am).
Klout is now focussing on topic-related Klout scores, so in the future it could get fine-grained enough for that sort of distinction.
I am wagering that we’ll be seeing a lot of this at SxSW next year.
At the moment, this seem like the web equivalent of knowing the doorman at the popular clubs. In practice, it means you are connected online, are ready to mix and mingle, and ready to converse knowledgeably on a wide range of topics.
Klout groups me with Paul Kedrosky, Jay Rosen, and Umair Haque. Cool. People I truly admire, and who influence me.
Stephanie Rosenblum via NY Times
How does one become an influencer?
After analyzing 22 million tweets last year, researchers at Hewlett-Packard found that it’s not enough to attract Twitter followers — you must inspire those followers to take action. That could mean persuading them to try Bikram yoga, donate to the Sierra Club or share a recipe for apple pie. In other words, influence is about engagement and motivation, not just racking up legions of followers.
Industry professionals say it’s also important to focus your digital presence on one or two areas of interest. Don’t be a generalist. Most importantly: be passionate, knowledgeable and trustworthy.
Still, scoring is subjective and, for now, imperfect: most analytics companies rely heavily on a user’s Twitter and Facebook profiles, leaving out other online activities, like blogging or posting YouTube videos. As for influence in the offline world — it doesn’t count.
Mr. Azhar, of PeerIndex, calls this “the Clay Shirky problem,” referring to the writer and theorist who doesn’t use Twitter much. “He’s obviously massively influential,” Mr. Azhar said, “and right now he has a terrible PeerIndex.”
More broadly, Mr. Schaefer of Schaefer Marketing and others are concerned that we are moving closer to creating “social media caste systems,” where people with high scores get preferential treatment by retailers, prospective employers, even prospective dates.
We are moving into neo-tribalism, not some pan-democratic, egalitarianism. Why are people continuously surprised that the web is not a great leveler, but instead a redistribution of authority, and that not everyone will wind up with equal reputation?
PS I am still rooting for betweeness (degree of connection) instead of eigenvalues (popularity) to get down to the dark matter of influence (see It’s Betweenness That Matters, Not Your Eigenvalue: The Dark Matter Of Influence).
Twitter is on a fast growth path, as shown by recent data, but then the same data show Tumblr growing even faster.
What’s the story?
Ultimately, everything important will appear in the streams first — like the stream of URLs in Twitter, and the stream of reblogs and likes in Tumblr — and those companies that own the streams will be in the best position to provide the complete liquid media user experience to users.Twitter and Tumblr strongly diverge in their treatment of tags. Tumblr has implemented tags as first class metadata, explicitly supported by the Tumblr system, while Twitter continues to treat tags as microsyntax: text conventions invented by users, embedded in the messages. And I think this is a mistake for Twitter, and for the community.
You might counter my claim by saying, “Hey, wait! I use hashtags all the time, and so do others! Twitter supports their use!” But you’d be wrong. Twitter treats hashtags as text, just like all the other characters in a tweet. So if you write a tweet like this —
@JohnFontana: @DeepakChopra channeling his inner @stoweboyd #140conf
— and the ‘#140conf’ text represents that the tweet pertains to the 140 Character Conference (where I spoke yesterday, and so did Deepak Chopra). The important thing to realize is that Twitter does nothing special with the hashtag: it merely retrieves tweets that have that text in them during searches. Period.
Contrast that with the convention of the at sign (‘@stoweboyd’ ‘@deepakchopra’) that originally arose from users indicating who a tweet was intended for, but which Twitter adopted and built into the system at a deep level. Ditto for retweets, which was originally ‘RT’ text, and now is now implemented operationally, as a kind of message. Not so with tags.
Tumblr, on the other hand, like most blogging tools, has rich and deep support for tags. In the editor, the user can add tags to posts:
And knowledgeable users can take advantage of the tags, for example, typing in the URL to access posts with a certain tag, like ‘www.stoweboyd.com/tagged/curation’, which leads to Tumblr creating a tag page (or pages) with all the posts with the tag.
Perhaps even more interesting is the recent push by Tumblr to integrate tags with curation in the relatively new Explore capability. Basically, Tumblr has decided that a list of a few dozen very popular and broad categories — like ‘Tech’, ‘LOL’, ‘Comics’, and ‘Fashion’ — should be curated by a mix of algorithm and editorial oversight. Like a media company might do.
Below, you can see the Explore page for Tech, with the Featured tab selected. This is the view that is curated by a group of Editors, selected by Tumblr’s staff, and provided a different version of the Tumblr dashboard (something I have yet to see, either directly on in a write-up).
You can see that I am featured as a Top Contributor this morning, along with Smarter Planet and a bunch of other folks.
Note that I carefully called the Tech page on Explore a category, and not a tag, per se. I think that what Tumblr has done is create a mapping from a long long list of tags, like ‘apple’ ‘pc’ ‘iphone’ and ‘twitter’, and mapped that to the Tech category. That means I don’t have to explicitly tag my posts as ‘tech’ to be included.
And tags can be pulled from across the entire Twitter universe, using URLs like ‘www.tumblr.com/tagged/paris’ or ‘www.tumblr.com/tagged/liquid_media’. These are examples of tags that have not been promoted to curated categories, like ‘Tech’ or ‘Fashion’, but in the future, Tumblr could always expand the roster of curated categories.
So, Twitter could learn from this in the following ways:
Point 3 — where Twitter builds and manages its own liquid curation system, right in the Twitter application, as another set of Twitter owned-and-operated streams — is an enormous opportunity for Twitter, and one that would drive a stake in the heart of a dozen start-ups that are trying to make a business around topical influence on Twitter, like Klout, or media businesses, like Flipboard, Xydo, and News.me. But Twitter has not showed any reluctance in clobbering the ecosystem of quasi-parasitic companies living lamprey-like on the Twitter underbelly.
And, if coupled with a few other flourishes — like Flipboardish social journal display based on the URLs in the stream — Twitter could also destabilize the tablet media market pretty dramatically, and increase the company’s valuation dramatically.
By exploiting tags and their role in curation, and quietly repositioning the company as a media player, Tumblr is a giant step ahead of Twitter.Ultimately, everything important will appear in the streams first — like the stream of URLs in Twitter, and the stream of reblogs and likes in Tumblr — and those companies that own the streams will be in the best position to provide the complete liquid media user experience to users.
By exploiting tags and their role in curation, and quietly repositioning the company as a media player, Tumblr is a giant step ahead of Twitter.
[Update: 17 June 3:41pm EST — I have been informed by a commenter that hashtags are parsed by Twitter, and any hashtags embedded in the text of a tweet are accessible. But my real point stands: Twitter doesn’t develop that into a rich user experience. And the other ways that hashtags could be used in the API — like given a hashtag, show me all the tweets using it — would have to be implemented by an external program.]
Mathew Ingram reports on the continuing efforts of various web services to decipher influence:
Mathew Ingram, The Race to Build a PageRank for the Social Web Continues
Both PeerIndex and Klout rank users based on data that comes from their Twitter, Facebook and LinkedIn accounts, although the two sites describe their rankings somewhat differently. Klout talks about overall “reach” and “amplification,” both of which are determined by looking at a user’s activity and how much impact it has on their social graph — whether their tweets are re-tweeted by others with influence, for example. PeerIndex says that it looks at a user’s activity in Twitter, Facebook and LinkedIn and then comes up with an authority rank for their expertise in eight topic areas, which it uses to create an influence “footprint” for each user.
As Klout and PeerIndex add more sources of reputation or influence data such as Quora to their rankings, the web moves closer to having a kind of Google PageRank for social activity, with all that implies. The big problem, as with Google search, is how to exclude the social equivalent of black-hat SEO and link spam, and how to determine what it is real influence and what is simply Justin Bieber-style popularity.
You are who you follow.
I continue to believe that these tools are motivated by a skewed model of what is going on online. It’s a sort of neo-classical economics viewpoint, where are individuals are considered as interchangeable, like replacement parts on an assembly line, or atoms banging into each other in a tea kettle of boiling water. And worse, they are considered in isolation, not as connected to others in a deep way.
We are social beings, and our social value is an emergent property of the network we are situated in, not a personality trait. We need to think about this issue in terms of position in the social network — who we follow and are followed by — not purely statistically.
Stowe Boyd, It’s Betweenness That Matters, Not Your Eigenvalue
Betweenness is a measure of how short are the chains that connects a person to the totality of the network. Like PageRank, betweenness is recursive: the people with the highest betweenness are likely to be connected to other people with high betweenness.
This means people are influential because they are connected to many influential people. But influence doesn’t seem directly linked to how many people you are connected to. It’s a function of being connected to others who have short chains to many other people with high betweenness. Or, looked at differently, betweenness is a measure of how many social circles, or social scenes, a person is connected to.
So, it’s not who you know, it’s where you know. It’s where you are situated in the network, and not just in the limited sense of how many immediate contacts you have.
The subtle, dark-matter mystery of social networks is that influence is oblique, and not easily determined by the sorts of tools we have today.
It is not your follower count, or who you follow, per se. But, instead, do you have short paths into other social scenes, both incoming and outgoing? That is the deep structure of being truly connected: bridging over different social scenes, acting as a conduit, a vector, a filter and amplifier for ideas good and bad, the best insights, and deadly viruses.
I maintain that the best predictor of an individual’s social value and the likelihood that their social activities will make an impact on others is who they are connected to, and in particular, who they follow. Following people from a diverse range of social scenes — different parts of the global social network — increases the likelihood that you will encounter new insights, new thoughts. And following more people who are connected themselves to diverse social scenes increases that likelihood. And that increases your social value to others.
You are who you follow.
Attempts to quantify our influence — our social value — without taking this into account are doomed to be a second order reflection of what is actually happening between us. It’s like trying to figure out why someone threw a rock into a stream by calculating the rock’s weight, trajectory, and the spread of the ripples. All very interesting, but it doesn’t get to why.
Adriaan Pelzer of Raak created someTwitter bots, that spewed interesting things at different periodicity, and discovered that Klout is broken.
The Klout Scores (the ugly)
For all practical purposes though, no matter how I look at it, Klout seems to be broken.
Consider the following Klout scores, for the four bots:
What’s wrong with this picture? To start off with, it should not really be possible for a bot to reach a Klout Score of 50 within 80 days merely by Tweeting random (yet entertaining) rubbish every minute, should it?
24 hours after the above klout scores were sampled, I took another set of samples, just to be sure:
Roughly the same result, except for huge fluctuations in transient metrics (see True Reach for Bot 1), which also seems a bit suspect. We can’t say for sure without knowledge of Klout’s exact algorithm.
The fact is, though, no matter how you look at it, unless Klout updates this aspect of their algorithm, in another 80 days Bot 1 could very well have the same Klout Score as @scobleizer!
Taking into account that many Twitter clients (like Hootsuite) and filter applications (like Datasift) are using Klout as a trusted way of filtering tweets, it means Klout will have to up their game on this one to stay in the game.
Yes, and the solution to fixing Klout is not just to figure out how to detect bots, but to discover a true metric of influence (see more on influence).
Gives ‘elevator pitch’ a whole new meaning: companies are trying to pitch their tents in the same building as Twitter.