The years 2011-2012 saw a huge rise in social sharing and its effects on search.Google, in particular, began to incorporate a huge number of social signals into its search results.
Commonly referred to as "Fresh Rank," search engines use the freshness signals of links to judge current popularity and relevance.
The last few years have seen an explosion in the amount of content shared through social services such as Facebook, Twitter, and Google .
Using sophisticated link analysis, the engines can discover how pages are related to each other and in what ways.
Since the late 1990s search engines have treated links as votes for popularity and importance in the ongoing democratic opinion poll of the web.
In order to weed out this irrelevant content, search engines use systems for measuring trust, many of which are based on the link graph.
Earning links from highly-trusted domains can result in a significant boost to this scoring metric.
A site like Wikipedia has thousands of diverse sites linking to it, which means it's probably a popular and important site.
To earn trust and authority with the engines, you'll need the help of other link partners. The concept of "local" popularity, first pioneered by the Teoma search engine, suggests that links from sites within a topic-specific community matter more than links from general or off-topic sites.
The potential power of this shift towards social for search marketers is huge.
Someone with a large social circle, who shares a lot of material, is more likely to see that material (and her face) promoted in search results.
Authority models, like those postulated in the Hilltop Algorithm, suggest that links are a very good way of identifying expert documents on a given subject. To answer this, we need to explore the individual elements of a link, and look at how the search engines assess these elements.