We need data for @matchFWD.

A lot.

We need data to help us suggest the best  talent matches for an open job opportunity to our connectors.

We’re only 2 developers, and I spend too much time not coding so we need help.

There’s currently 2 API that buzzed trying to evaluate influence, reach, reputation and authority of Twitter users : Klout and PeerIndex.

I am not really interested by most metrics right now, but I want to know what topics a user tweet about. Lucky for me both API have such a method so I ran a small manual test on Twitter users I know and follow well enough to judge the results

Here are the results…

Ben Yoskovitz (byosko)

• Klout : ”Entrepreneurship”,”social media”,”Human Resources”
• PeerIndex : “private equity”,”venture capital”,”finance”,”marketing”,”montreal”

GeorgesDuverger

• Klout : “Montreal”,”Yul”,”Developers”
• PeerIndex : “free software”,”realtime web”,”google chrome”,”science”,”api”

Carl Mercier (cmercier)

• Klout : “Montreal”,”Met”,”technology”
• PeerIndex : “databases”,”data management”,”digital media”,”ipad”,”iphone”

DavidDesjardins

• Klout : nothing….
• PeerIndex : “cycling”,”andy schleck”,”bessette”,”bicycle sharing system”,”cervlo”

Martin Dufort (mdufort)

• Klout : “iPhone”,”Apple”,”Google”
• PeerIndex : “iphone”,”cloud clients”,”embedded linux”,”apple tv”,”nexus”

Seb Provencher (sebprovencher)

• Klout : ”"Montreal”,”Marketing”,”Quebec”
• PeerIndex : “marketing”,”mass media”,”realtime web”,”digital media”,”bing”

Alex Dao (alexdao)

• Klout : “Montreal”,”Retailers”,”Regions”
• PeerIndex : “montreal”,”realtime web”,”google search”,”marketing”,”villemarie montreal”

Myself

• Klout : “Quebec”,”Techno”,”Francophone”
• PeerIndex : “mass media”,”collaboration”,”marketing”,”community websites”,”criticism of facebook”

Klout seems to limit the number of topics to three and is much more generic. If I had to classify my users in large bucket, that could be interesting but it wouldn’t make it easier to identify specifically everyone in my twitter feed.

PeerIndex results are much more precise and diverse. The downside, I would guess without testing, is that they are probably much more volatile. The topics you rank for this week, won’t be next week topics… So how do you deal with this… You weight all tags you attach to your users ?

What am I going to use ? Most probably both. Now let’s it Stackoverflow API and GitHub API to find great developers…

Do you use these ? How ?

Related articles

• Who needs Whuffie – What’s your PeerIndex at Le Web? (techcrunch.com)
• Real vs Faux ‘Influence’ and why Klout Matters (enterpriseirregulars.com)
• Klout Gets $8.5M to Create the Page Rank of the Social Web (gigaom.com)
• Your Klout and PeerIndex Are Something, But Not Everything (scrapsofmygeeklife.com)

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Merci Internet

PS : tell me about you

To do that, you first need to determine who has some influence online around that topic. There is currently multiple web services to evaluate user ranking, and I’ve reviewed some here. Klout is another of those services and a pretty popular one. Main problem with most of them is that they usually have no concept of relevancy : they evaluate your reach, influence, activity and other parameters as a generic score, without any relation to a topic or domain of influence.

I’ve just performed a search for ‘Django’ in Klout’s topics search box. Number one influencer on this somewhat niche topic is … Tara Hunt aka MissRogue. For those who might not know here, MissRogue is a successful author/marketing consultant/entrepreneur with a somewhat decent audience of … 29757 (Dec 1st 2009)followers on Twitter. She probably knows more about Django than the average person, but I would have expected Jacob Kaplan-Moss or some of the bloggers in my Django links collections to be slightly above her in such ranking…

klout django influencers

What happened is probably that she tweeted that keyword several days ago and the Klout engine pick it up, putting here in their Django topic basket and by looking at the outstanding number of followers she has, promoted her to the top of the list. A more complete analyze of her tweets would have been enough to avoid this error. Further analysis of shared link would be even better, but slightly more complex.

User Ranking methods and technology will most certainly become ubiquitous in a near future and evolve into something solid and relevant enough to be used as a content and conversation filter, as well as for targeted advertising purposes. A great example of the relevancy concept can be found in Traackr from which I just got a demo. They still do some manual intervention for quality assurance, but they have included a relevancy score related to the queried domain, as I would expect. We talked a little bit about their roadmap and they seems to have some pretty interesting stuff coming up.

Are you planning to use some kind of User Ranking in your applications or web strategies ? How ? What are you expecting from such tools ?

Don’t get me wrong, I like Twitter and I use it all the time. But since it became the fastest growing channel, the number of real blog comments have dropped enormously. You often find yourself looking through rows of re-tweets that were collected by a Backtype or Disqus plugin at the bottom of a great post to realize that it was retweeted 30 times and commented once… Worse, how many times have you seen an heavily retweeted post with 0 comments ?

Retweeting shows appreciation but it’s gotten so easy, that it seems less and less users takes the time to join the conversation and comment. Not talking about adding  15 char to a retweet here. It’s probably true that Twitter increased the number of participants in those conversations, but they rarely add real value to it but simply passing it to their own network. Which is good but …

Looks like a great opportunity to show your favorite bloggers or new one you just found out about that you value their content and ideas. I am 100% sure they remember more easily comments that retweets… which could be a great opportunity to contact them if you have anything to ask or offer.