Do LinkedIn Recommendations Matter In the Reputation Economy?

There is an interesting conversation going on this week between some of the web’s heavy hitters on the subject of the actual value of LinkedIn recommendations in the reputation economy.

Here’s the time line of the conversation so far…

• July 17th – Jeremiah Owyang (Forrester Research) posts a thought provoking and well-written piece on his blog that sparks the debate titled Requested Recommendations on Social Networks: Why I Won’t Do It
• July 17th, later that day – Russ Somers (Egghead Marketing) posts an extended the conversation on his blog about the  Evaluating LinkedIn Reccomendations that references Jeremiah’s article and the resulting Twitter chatter.
• July 18th – Kay Luo, Sr. Director of Corporate Communications at LinkedIn, contacts Jeremiah and writes him a LinkedIn recommendation that he accepts on his profile.
• July 24th, LinkedIn responds to Jeremiah’s post on their blog, discussing the benefits of recommendations and the social economy.

Here are some of the highlights from the conversation…

From Jeremiah’s Post –

Why [LinkedIn] Recommendations May Not Be Trusted
From time to time, former colleagues ask me to be their reference –or even do recommendations (online references or testimonials) for them on social sites, like LinkedIn. Yet having gone through this process, they aren’t that trustworthy, here’s why:

Filter One: I question how honest and authentic recommendations are when the system primarily has features that vet out unwanted reviews. In nearly every experience I’ve been in, a former colleague or someone I’ve worked with requests a recommendation, this means they are expecting a positive review. Since the content is in public, saying something bad about someone else (even if it’s true) isn’t going to help your network, so the the contributor is biased.

Filter Two: Then, they can review my submitted review, and then accept or reject. I’ve had someone reject my reference, and ask me to rewrite it once before (I think it may have been because I had a typo). Because these three filters are setup, it’s unlikely that you’ll see reviews that are have objective content, or negative information.

Now it’s not just recommendation systems in business social networks, it’s also case studies from vendors, and customer testimonials. All of this content is cleaned, scrubbed, and presentable in favor the seller.

Key Takeaways from Jeremiah’s Post…

• Recommendations that are vetted by the requestor will  never be fully viewed as objective –savvy buyers know that, and can figure out how to get the information through private conversations or other reviews.
• Recommendations still matter, but who they come from, and in what context matters ever more, indicating you liked working with someone is still valuable –even if they are filtered.
• Buyers should look for references (positive and negative) from more organic locations like blogs and Twitter, where the candidate/seller has less control over filtering and scrubbing the content.
• Candidates and sellers need to prepare for the open reviews of good –and bad–reviews about their company and resume.
• LinkedIn [is] very valuable, and has many other features of note. This isn’t a knock on them, but instead on the marketing and pitching process in general.

From LinkedIn’s Response…

Adam Nash reminds us that “Transparency Is The New Objectivity“, that people “consider the source  as well as the context” of recommendations and quotes David Weinberger:

“What we used to believe because we thought the author was objective we now believe because we can see through the author’s writings to the sources and values that brought her to that position. Transparency gives the reader information by which she can undo some of the unintended effects of the ever-present biases. Transparency brings us to reliability the way objectivity used to.

This change is, well, epochal.”

Key Takeaways from LinkedIn’s post…

• Reputation matters. On LinkedIn, your profile and reputation is tied to every recommendation you make.  As  a result, people can and do consider the source.  Having someone say you are a Web 2.0 visionary is fine and dandy, but those exact words coming from Jeremiah Owyang means something different.
• Transparency matters. It’s trivial to see how many recommendations a person has given, and whether they tend to write the same things about everyone.  It’s also fairly trivial to see the relationship between the person being recommended and the source.
• Content matters. Which recommendations a person publishes is up to the individual.  As a result, you won’t find “negative recommendations” (isn’t that an oxymoron?) on the site, any more that you would expect a person giving references for a job to give you people who think poorly of them.  However, recommendations speak volumes in terms of what they do and don’t say (the post links to this recommendation for Peter Thiel from Reid Hoffman)

Additional Thoughts

There were great points made on both sides of this debate, and if you’re interested in this topic, I’d suggest heading over to either Jeremiah’s post or the LinkedIn response to join the conversation (after all, that’s where the conversation is happening).

My stance on the matter after reading the entire conversation is that Jeremiah’s concerns are valid and his arguments are strong. You’ve got to question the motivations and authenticity of every recommendation that you read and be skeptical. The fact that the system allows for manipulation of how recommendations are displayed by the recommendee (the ability to accept or reject) definitely dilutes the perceived value of the recommendation system in general.  That said, and these were great points by LinkedIn – 1) they’re called recommendations to reflect how the system is supposed to work, and for a reason (“negative recommendations” is an oxymoron) and 2) we all acknowledge how the system works and naturally apply our own skepticism and filters to the process by evaluating the source and context when we read these things (you’d be a fool not to).

The real question that all this raises for me is, could we improve recommendation systems like LinkedIn’s by making them more democratic and open? Would the ability to “thumb down” a person or post a negative comment that hurt their reputation lead to a mass exodus from the system (decreasing the value of the network overall). I don’t know the answer to those questions, but I think LinkedIn has done a good job of keeping the vibe positive through design, and that the control they offer users over recommendations, on avarage, improves the ecosystem more than it hurts it.