In 1998, two graduate students at Stanford University, Larry Page and Sergey Brin, developed "Backrub", a search engine that relied on a mathematical algorithm to rate the prominence of web pages. The number calculated by the algorithm, PageRank, is a function of the quantity and strength of inbound links. PageRank estimates the likelihood that a given page will be reached by a web user who randomly surfs the web, and follows links from one page to another. In effect, this means that some links are stronger than others, as a higher PageRank page is more likely to be reached by the random web surfer.
However I feel that batching all the things influencers share , filter whats relevant from whats not… and ultimately niche it down to identify which exact type of content is hot in order to build our own is a bit fuzzy. Influencers share SO MUCH content on a daily basis – how do you exactly identify the topic base you’ll use build great content that is guaranteed to be shared?
If you havent see it already, check out the links in shor's comment below - there are some great resources in there. In some cases you can also consider surveying your current audience or customers through email, on-site surveys or SurveyMonkey. Be sure to ask for some profiling information that you can use for determining specific persona needs like age, sex, location, etc. (Probably best not to make it sound like a creepy text chat like I just did though...) :)
If you are using Responsive Web Design, use meta name="viewport" tag to tell the browser how to adjust the content. If you use Dynamic Serving, use the Vary HTTP header to signal your changes depending on the user-agent. If you are using separate URLs, signal the relationship between two URLs by tag with rel="canonical" and rel="alternate" elements.