Name
Abstract | ||
|---|---|---|
Knowledge about the general graph structure of the World Wide Web is important for understanding the social mechanisms that govern its growth, for designing ranking methods, for devising better crawling algorithms, and for creating accurate models of its structure. In this paper, we describe and analyse a large, publicly accessible crawl of the web that was gathered by the Common Crawl Foundation in 2012 and that contains over 3.5 billion web pages and 128.7 billion links. This crawl makes it possible to observe the evolution of the underlying structure of the World Wide Web within the last 10 years: we analyse and compare, among other features, degree distributions, connectivity, average distances, and the structure of weakly/strongly connected components. Our analysis shows that, as evidenced by previous research, some of the features previously observed by Broder et al. are very dependent on artefacts of the crawling process, whereas other appear to be more structural. We confirm the existence of a giant strongly connected component; we however find, as observed by other researchers, very different proportions of nodes that can reach or that can be reached from the giant component, suggesting that the "bow-tie structure" is strongly dependent on the crawling process, and to the best of our current knowledge is not a structural property of the web. More importantly, statistical testing and visual inspection of size-rank plots show that the distributions of indegree, outdegree and sizes of strongly connected components are not power laws, contrarily to what was previously reported for much smaller crawls, although they might be heavy-tailed. We also provide for the first time accurate measurement of distance-based features, using recently introduced algorithms that scale to the size of our crawl. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1145/2567948.2576928 | WWW (Companion Volume) |
Keywords | Field | DocType |
accurate model,billion web page,bow-tie structure,heavy tail,crawling algorithm,general graph structure,underlying structure,billion link,crawling process,accessible crawl,World Wide Web | Data mining,World Wide Web,Web mining,Crawling,Ranking,Web page,Computer science,Power graph analysis,Giant component,Heavy-tailed distribution,Strongly connected component | Conference |
Citations | PageRank | References |
36 | 1.56 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert Meusel | 1 | 234 | 16.62 |
| Sebastiano Vigna | 2 | 2731 | 153.47 |
| Oliver Lehmberg | 3 | 179 | 9.59 |
| Christian Bizer | 4 | 8448 | 524.93 |