Google was founded in 1998 to solve a specific technical problem: early web search engines often returned long, unreliable lists because they relied heavily on matching keywords in pages. Larry Page and Sergey Brin, two PhD students at Stanford University, built a search system that treated links between pages as evidence of importance. Their core idea, PageRank, helped organize the rapidly growing web by ranking pages using the structure of hyperlinks, and it changed what people expected from internet search.
PageRank started from an observation about the web’s design. A hyperlink is not only a path to another page; it is also a decision made by an author. If many independent pages link to a page, that page is more likely to be valuable. Page and Brin described this approach in their 1998 paper “The Anatomy of a Large-Scale Hypertextual Web Search Engine,” which explained how they combined link analysis with text matching. The key shift was to treat the web as a graph, meaning a network of nodes (webpages) connected by directed edges (links). This mattered because it allowed ranking to use global structure, not just local word counts.
The PageRank algorithm assigns each page a score based on links from other pages, and it weights those links by the importance of the linking pages. A link from an authoritative site counts more than a link from an obscure one, because authority is passed through links. In practical implementations, PageRank is computed by iterative calculation until scores stabilize, reflecting the idea of a “random surfer” who clicks links. A damping factor, often described around 0.85 in academic explanations, models the chance that the surfer stops following links and jumps to a random page, which prevents traps like infinite loops in tightly linked clusters. The importance is not the exact constant but the engineering principle: ranking must remain stable on a huge, messy graph.
PageRank did not replace keyword search; it made keyword search far more useful by improving ordering. In the 1990s, engines such as AltaVista (launched in 1995) could index large parts of the web, but relevance ranking was frequently weak because many pages shared similar terms, and some publishers manipulated visible text. Google’s early system combined traditional information retrieval signals, such as whether the query terms appeared in titles and headings, with PageRank-based authority. When two pages both matched the words, the link-based score helped decide which one a user likely wanted. This mattered because “relevance” is not only about matching words; it is also about trust and context.
Google’s founding turned this research into an operating company. Page and Brin incorporated Google in California on September 4, 1998, after building an earlier Stanford project called BackRub in 1996. Early funding included a well-known $100,000 check from Andy Bechtolsheim, a co-founder of Sun Microsystems, and the company soon moved out of a garage in Menlo Park. These details matter because they show how quickly a university prototype became infrastructure: search quality improvements created user demand, and user demand justified the cost of building larger indexing and ranking systems.
Scaling PageRank to the whole web required distributed computing and careful data engineering. The algorithm depends on knowing large portions of the link graph and recalculating ranks as the web changes. Google built systems to crawl pages, store link data, and compute rankings across many machines, turning the web into a continually updated dataset. This was one reason Google became associated with data centers and large-scale computation long before “big data” became a common term. The broader lesson is that a strong algorithm alone is not enough; it must be paired with an architecture that can process billions of pages reliably.
PageRank also reshaped incentives on the web, for better and worse. Because links influenced ranking, website owners began pursuing inbound links to gain visibility, and a market for manipulation emerged, including link farms and paid links. Google responded over time with additional ranking signals and anti-spam measures, but the core pattern remained: search ranking affects business outcomes, which motivates attempts to game the system. This matters today because it explains why modern search uses many signals beyond PageRank, including freshness, location, and assessments of page quality, while still benefiting from link-based notions of authority.
The lasting impact of Google’s 1998 founding is that it normalized the idea that search should organize information by analyzing relationships, not just by scanning text. PageRank made the web’s link structure computationally useful and pushed search toward ranking that feels like a judgment about credibility. That influence continues in current debates about how search engines shape knowledge, commerce, and politics, and why transparency and resistance to manipulation remain central technical and social challenges.