One of the consequences of the PageRank algorithm and its further manipulation has been the situation when backlinks (as well as link-building) have been usually considered black-hat SEO. Thus, not only Google has been combating the consequences of its own child's tricks, but also mega-sites, like Wikipedia, The Next Web, Forbes, and many others who automatically nofollow all the outgoing links. It means fewer and fewer PageRank votes. What is then going to help search engines rank pages in terms of their safety and relevance?
Totally agree — more does not always equal better. Google takes a sort of ‘Birds of a Feather’ approach when analyzing inbound links, so it’s really all about associating yourself (via inbound links) with websites Google deems high quality and trustworthy so that Google deems YOUR web page high quality and trustworthy. As you mentioned, trying to cut corners, buy links, do one-for-one trades, or otherwise game/manipulate the system never works. The algorithm is too smart.
Given that “only a tiny percentage of links on the Web use nofollow”, why don’t we just get back to focusing on humans and drop nofollow? It has failed, and given that all it ever was was a tool to manipulate Pagerank, it was bound to do so. Has Google done any tests on its search quality taking nofollow into account vs. not taking it into account, I wonder?
My favorite tool to spy on my competitors' backlinks is called Monitor Backlinks. It allows you to add your four most important competitors. From then on, you get a weekly report containing all the new links they have earned. Inside the tool, you get more insights about these links and can sort them by their value and other SEO metrics. A useful feature is that all the links my own website already has are highlighted in green, as in the screenshot below.
where N is the total number of all pages on the web. The second version of the algorithm, indeed, does not differ fundamentally from the first one. Regarding the Random Surfer Model, the second version's PageRank of a page is the actual probability for a surfer reaching that page after clicking on many links. The PageRanks then form a probability distribution over web pages, so the sum of all pages' PageRanks will be one.
Moreover, the PageRank mechanism is entirely general, so it can applied to any graph or network in any field. Currently, the PR formula is used in bibliometrics, social and information network analysis, and for link prediction and recommendation. It's even used for system analysis of road networks, as well as biology, chemistry, neuroscience, and physics.
The Nielsen Global Connected Commerce Survey conducted interviews in 26 countries to observe how consumers are using the Internet to make shopping decisions in stores and online. Online shoppers are increasingly looking to purchase internationally, with over 50% in the study who purchased online in the last six months stating they bought from an overseas retailer.
There’s a lot of frustration being vented in this comments section. It is one thing to be opaque – which Google seems to be masterly at – but quite another to misdirect, which is what No Follow has turned out to be. All of us who produce content always put our readers first, but we also have to be sensible as far as on page SEO is concerned. All Google are doing with this kind of thing is to progressively direct webmasters towards optimizing for other, more reliable and transparent, ways of generating traffic (and no, that doesn’t necessarily mean Adwords, although that may be part of the intent).
PageRank was influenced by citation analysis, early developed by Eugene Garfield in the 1950s at the University of Pennsylvania, and by Hyper Search, developed by Massimo Marchiori at the University of Padua. In the same year PageRank was introduced (1998), Jon Kleinberg published his work on HITS. Google's founders cite Garfield, Marchiori, and Kleinberg in their original papers.
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