When web search services became popular in the 1990s, early search engines used internal content factors almost exclusively to rate the relevance and ranking of web pages. Rankings were thus childishly easy to manipulate. By inserting dozens of hidden keywords on a page, for example, an aggressive web page author could make a page seem richer in popular topic relevance than other web pages (“sex, sex, sex, sex”).
By the late 1990s even the largest search engines were considered marginally useful in locating the best sources of information on a given topic, and the top-ranked sites were often those that used the most effective manipulation techniques to bias the search engines. The innovation that transformed web search in the late 1990s was Google’s heavy use of external page factors to weigh pages’ relevance and usefulness.
Google’s algorithms balance external ranking factors with statistical analysis of the page text to determine relevance and search ranking. Google’s fundamental idea is similar to peer citations in academic publications. Every year thousands of science papers are published: How can you tell which articles are the best? You look for those that are most frequently cited (“linked”) by other published papers. Important science papers get cited a lot. Useful web sites get linked a lot.