A picture I see daily when I login to LinkedIn: Mr. ABC recommends Mr. XYZ and right under Mr. XYZ recommends Mr. ABC. The first writes how the guy was a great employee / contractor and in less than an hour the other one recommends his former boss / customer. And do not forget to include a lot of superlatives likes: phenomenal, amazing, rare, one of the few etc.
I was actually thinking about some screenshots to illustrate that but I do not want to insult anyone :o)
Would you trust such recommendations? Do people really think they have any value? But still, I see such scenarios almost daily. I still do not understand why people recommend someone just because the person asked them to do so. You can always ignore the request or politely decline. What happens is that you logically adjust your respect to a person that recommends someone you know and about whom you think is a schmuck.
Recently I got contacted by a lady I once met about 8 years ago in a pub, asking me about recommendation. I politely refused since even if I know her, I actually never worked with her. She replied that it is OK, that she understands, but she is trying to get some recommendations to her profile since nobody wants to invite her for interview without references.
Really? People actually decide about inviting a person for interview based on the amount of LinkedIn references? That is scary! Sometimes I also get CVs with proud statements in the intro letter like “I have 14 recommendations on LinkedIn!”. Who cares about the quantity if quality is questionable?
It’s like search engines before Google came. It was enough to have a particular word many times repeated on the page and even more times repeated in the keywords section to be displayed on top of search results. And then came the PageRank and suddenly you could really find relevant stuff on the web.
In order to make a meaning of the references, LinkedIn and other business networks need to think about some kind of “TrustRank” related to people. It could be a formula, calculated (pretty much like the PageRank) from different values from your network.
Here are some ideas about what the formula could contain:
- Probably it has to work against the principle of PageRank – the fact that someone is many times recommended doesn’t increase his/her credibility – it can just mean he/she annoys a lot of people to get recommended.
- Is should dramatically lower the credibility of people who “cross recommend” each other within a short period of time (a few hours / days?).
- It could capture people’s credibility, real achievements and reputation from other sources on the web and blend that in. I know a few people who rarely recommend anyone. And if they do, I tend to really trust them.
- If a person is recommended by a colleague or boss you could track how long they were working together before the recommendation was created.
- Recommendations closer to the end of someones job position should be also discounted since people tend to pro-actively ask for recommendations when looking for a new job (I’m not saying that is bad, just that recommendations might not have that high value as opposed to a spontaneous recommendation when someone impresses you with their job).
- The users in the network could (maybe anonymously) score and comment recommendations of other people in their network to share if they agree or not.
So far, I recommended only 2 people, both colleagues from ZOOM that I know for 5 and 8 years on respectively. You have only one reputation on the web, do you? And even deleted posts still shows in the results…
Happy to hear your comments.
