PageRank

PageRank was the insight that made Google work. Larry Page and Sergey Brin's thesis was that links between pages could be treated like academic citations: a page linked to by many other pages is likely more important than one rarely referenced. A link from an already-important page is worth more than a link from an unimportant one. They formalized this as a recursive scoring formula that propagates authority through the web's link graph — pages accumulate score from inbound links and pass fractional amounts to the pages they link to.

The algorithm uses a damping factor (historically 0.85) to model the probability that a random web surfer following links would keep clicking rather than jumping to a new random starting page. This prevents authority from inflating infinitely — it decays slightly through each link. The system converges to a stable score distribution across the entire link graph. A page with no inbound links has only its base damping factor score; a page with many high-authority inbound links accumulates significantly more.

Google stopped publishing public PageRank scores in 2016 (the visible toolbar was already discontinued in 2014). Third-party approximations — Moz's Domain Authority, Ahrefs' Domain Rating — model the same concept from observable link data, but they're not Google's internal scores and should not be treated as equivalent. Internal PageRank calculations continue to run; what changed is that practitioners can no longer see them directly.

The concept still matters practically because it explains the core logic underlying backlinks as a ranking signal: why quality matters more than quantity, why internal link architecture affects rankings, and why link equity dilutes through redirect chains and nofollow attributes. Understanding the model is more useful than treating DA or DR as ground truth — third-party metrics are proxies with their own biases, not direct reads of the signal they're approximating.