The encyclopedia · R&D & Science · Technical decision · 1997–1999
HITS ranked pages by who links to whom, not by their own words
Kleinberg's HITS scored every page twice — as authority and hub — so mutually endorsing pages rose without describing themselves.
Cornell University
The solution
Searching the early web by text failed on broad queries: Harvard's homepage does not use the word 'Harvard' most prominently, and search-engine homepages do not mention 'search engines'. Jon Kleinberg argued that hyperlinks encode human judgment about authority.
His HITS algorithm divides pages into hubs — pages that point to many good sources — and authorities — pages many hubs point to. Starting from a focused subgraph, it updates both scores in alternation: authorities inherit hub weight, hubs inherit authority weight.
Because the iteration converges to principal eigenvectors of the link matrix, the algorithm is mathematically stable and surfaces small communities of mutually reinforcing pages. Kleinberg first presented it at SODA 1998 and published the journal version in 1999.
Why it worked
- Links encode human endorsements that text cannot
- Hub/authority duality captures two different roles
- Eigenvector iteration converges to stable rankings
- Broad queries need structure, not just word counts
What can be applied
When content says nothing, judge by endorsements — and score the endorsers too. Mutual reinforcement turns many noisy links into a stable ranking, as long as you iterate to convergence.
Aftermath
HITS became a standard link-analysis method alongside PageRank and influenced search, recommendation and citation analysis; the hub/authority vocabulary is now part of web science.
Sources
- Authoritative Sources in a Hyperlinked Environment
- Authoritative Sources in a Hyperlinked Environment
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