Linkedin rolled out their one-click endorsement feature this past month. As I’ve traded clicks with friends and colleagues, I’ve been trying to figure out what their real goal is. On the surface, this feature feels redundant with their existing “recommendation” feature. Given their aggressive efforts to promote this new feature, the data they are gathering is clearly important to the development of the algorithms behind their services – but how?
Linkedin has been fairly quiet about the inner workings of their search engine. This is likely to prevent people from manipulating the results, since there is significant value in being on the first page of a Linkedin search for a lucrative professional skill. They share some basic pointers about how to “be visible” on their help page. Key points from their page:
- There is no single rank for Linkedin Search – results are unique to each user/query
- The profile keywords of both parties (searcher, results) play a significant role
- Rankings are adjusted based on how prior searchers have reacted to your profile
While the above metrics are fine for identifying which candidates are relevant to a search, they don’t rate candidate quality: who actually knows their stuff? What’s missing here is a broader assessment of “page trust” (graph model analysis concept) that candidates possess the skills that they reference on a profile. For example, Google’s search algorithm incorporates an evaluation of the credibility of a site using link patterns, brand signals, and social activity. With these new features, it looks like Linkedin may be trying to adapt Google’s Pagerank algorithm (or something similar) to ranking candidates for specific skillsets.