Power-Law Distribution of the World Wide Web

By Lada A. Adamic, Bernardo A. Huberman. Science, 2000

1,119 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/e50b64b496f3b5bc6eaf50a7f5d53fdae16bb946

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In Computer Networks and Communications

In Statistical and Nonlinear Physics

Citations in the corpus

Beyond Gaussian averages: redirecting international business and management research toward extreme events and power laws (2007, background): “…Italian industrial districts Transition economies Casti (1994) Zipf (1949); Abrams and Strogatz (2000) Albert et al. (1999) Faloutsos et al. (1999) Adamic and Huberman (2000) Dezsö et al. (2006) Aiello et al. (2000); Ebel et al. (2002) Watts (2003) Liljeros et al. (2001) Barabási and Bonabeau…”
Topical interests and the mitigation of search engine bias (2005, background): “For a quantitative deﬁnition of popularity we turn to the probability that a generic user clicks on a link leading to a speciﬁc page [10].”
The “New” Science of Networks (2004, result): “…and breaking ties after joining the network (Bornholdt & Ebel 2001), then any value of the exponent between 2 and 3 can be obtained—a result that, unlike the singular in the original BA model, older nodes are not necessarily better connected than more recent additions (Adamic & Huberman 2000).”
Peer-to-peer architecture case study: Gnutella network (2001, background): “Recent research [1,7,8,13] shows that many natural networks such as molecules in a cell, species in an ecosystem, and people in a social group organize themselves as so called power-law networks.”
Synchronization in scale-free dynamical networks: robustness and fragility (2001, background): “In the case of the World Wide Web (WWW), the nodes are Web sites and they are joined when there is a hyper-link from one to the other [2-6].”
Enterprise Social Media: Definition, History, and Prospects for the Study of Social Technologies in Organizations (2013, background): “We know, for example, that a small fraction of users account for the most content in online communities (Adamic & Huberman, 2000), and this power law distribution holds for public social media such as blogs and microblogs (Java, Song, Finin, & Tseng, 2007).”
The Structure and Function of Complex Networks (2003, background): “This does not mean that preferential attachment is not the explanation for power-law degree distributions in the Web, only that the dynamics of the Web must be more complicated than this simple model to account also for the observed age distribution [35].”
Synchronization and desynchronization of complex dynamical networks: an engineering viewpoint (2003, background): “The other way in which E‐R models differ from most real-world networks is their degree distributions [2], [4], and [ 5 ]: many familiar networks, including the Internet, the World Wide Web, and power grids, etc., appear to have power-law degree distributions, while E‐R models only provide either bin”