{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T22:50:33Z","timestamp":1790981433374,"version":"4.1.0"},"reference-count":25,"publisher":"National Academy of Sciences","issue":"8","content-domain":{"domain":["www.pnas.org"],"crossmark-restriction":true},"short-container-title":["Proc. Natl. Acad. Sci. U.S.A."],"published-print":{"date-parts":[[2002,4,16]]},"abstract":"<jats:p>As a whole, the World Wide Web displays a striking \u201crich get richer\u201d behavior, with a relatively small number of sites receiving a disproportionately large share of hyperlink references and traffic. However, hidden in this skewed global distribution, we discover a qualitatively different and considerably less biased link distribution among subcategories of pages\u2014for example, among all university homepages or all newspaper homepages. Although the connectivity distribution over the entire web is close to a pure power law, we find that the distribution within specific categories is typically unimodal on a log scale, with the location of the mode, and thus the extent of the rich get richer phenomenon, varying across different categories. Similar distributions occur in many other naturally occurring networks, including research paper citations, movie actor collaborations, and United States power grid connections. A simple generative model, incorporating a mixture of preferential and uniform attachment, quantifies the degree to which the rich nodes grow richer, and how new (and poorly connected) nodes can compete. The model accurately accounts for the true connectivity distributions of category-specific web pages, the web as a whole, and other social networks.<\/jats:p>","DOI":"10.1073\/pnas.032085699","type":"journal-article","created":{"date-parts":[[2002,7,26]],"date-time":"2002-07-26T10:45:09Z","timestamp":1027680309000},"page":"5207-5211","update-policy":"https:\/\/doi.org\/10.1073\/pnas.cm10313","source":"Crossref","is-referenced-by-count":295,"title":["Winners don't take all: Characterizing the competition for links on the web"],"prefix":"10.1073","volume":"99","author":[{"given":"David M.","family":"Pennock","sequence":"first","affiliation":[{"name":"NEC Research Institute, 4 Independence Way, Princeton, NJ 08540; and School of Information Sciences and Technology and Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16801"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gary W.","family":"Flake","sequence":"additional","affiliation":[{"name":"NEC Research Institute, 4 Independence Way, Princeton, NJ 08540; and School of Information Sciences and Technology and Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16801"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Steve","family":"Lawrence","sequence":"additional","affiliation":[{"name":"NEC Research Institute, 4 Independence Way, Princeton, NJ 08540; and School of Information Sciences and Technology and Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16801"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric J.","family":"Glover","sequence":"additional","affiliation":[{"name":"NEC Research Institute, 4 Independence Way, Princeton, NJ 08540; and School of Information Sciences and Technology and Department of Computer Science and Engineering, Pennsylvania State University, University Park, PA 16801"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C. 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