We have added Linkedin’s influencers to our score, so that people considered expert or leader in a field by Linkedin are also measured on Alianzo. We use data such as views per post, comments or likes in order to classify Linkedin’s influencers.

There are around 430 influencers on Linkedin (sorry, by invitation only), some of them as famous as Richard Branson, Barack Obama, David Cameron or Bill Gates. I believe we are the first site on the Internet to use this data to rank people, which shows are deep effort to innovate and increase the quality of our scores.

Linkedin orders its influencers by the number of followers they get. We use many more data. If the influencer is being very active and his readers are replying, commenting and liking his posts, he will get a higher score.

Ranking people on Linkedin is not easy, as the closeness of this network does not put things easy. In spite of that, we have tried hard, and we think we have been able to build a good top of Linkedin users. Instead of basing it on the number of connections, which is relatively easy to manipulate, we are using activity data, both of the user (frequency of posts) and its followers (likes, comments), and in the case of influencers, also the number of followers.

This explains why the algorithm has suffered a big change and top positions are now occupied by Linkedin VIPs. For the rest of the users, connections and recommendations are still being used, but we are also ranking people based on their activity and that of their friends. So if you post frequently on Linkedin and you get enough reactions from your connections, you are probably going to rank higher.

Besides that, we are not crawling data at the same speed for everybody. If you are a heavy user, we will be updating your data at least once every day. Otherwise, we won’t be doing it and you could notice that data are not so acurate for your profile. Besides, you should connect your Alianzo account with your Linkedin profile, as some of these data are not available for not connected users.

The problem with connections and recommendations is that it is very easy to manipulate it by asking friends to connect and recommend you. So this data is not so good for ranking Linkedin users. We are using it, though, but the algorithm has lowered its importance.

Besides, it’s not always so easy to know the real number of connections a user has. Linkedin does not show this information and does not provide more than 3,000 lifetime connection requests for its users. Otherwise, you must have people requesting you to become their connections, even if you don’t know them.

By parsing some pages, we got to get the real data for many Linkedin members, but there were some where we had no way to do it. So when you read in a blog that X or Y (for example, Steven Burda) is the top Linkedin user, this information is not really so acurate. It’s known that there are heavy LinkedIn Open Networkers (LIONs), but there is no list of them.

There are some users who work hard to acquire connections and recommendations, but it’s really hard to know who got the most and how important these people became in order to rank them. Not even them get to know how useful having lots of Linkedin connections can become in real life, besides getting lots of requests every day.