The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Proceedings of the 9th international World Wide Web conference on Computer networks : the international journal of computer and telecommunications netowrking
ANF: a fast and scalable tool for data mining in massive graphs
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The webgraph framework I: compression techniques
Proceedings of the 13th international conference on World Wide Web
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Planetary-scale views on a large instant-messaging network
Proceedings of the 17th international conference on World Wide Web
On compressing social networks
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
HyperANF: approximating the neighbourhood function of very large graphs on a budget
Proceedings of the 20th international conference on World wide web
Robustness of social networks: comparative results based on distance distributions
SocInfo'11 Proceedings of the Third international conference on Social informatics
Proceedings of the 3rd Annual ACM Web Science Conference
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We recently measured the average distance of users in the Facebook graph, spurring comments in the scientific community as well as in the general press ("Four Degrees of Separation"). A number of interesting criticisms have been made about the meaningfulness, methods and consequences of the experiment we performed. In this paper we want to discuss some methodological aspects that we deem important to underline in the form of answers to the questions we have read in newspapers, magazines, blogs, or heard from colleagues. We indulge in some reflections on the actual meaning of "average distance" and make a number of side observations showing that, yes, 3.74 "degrees of separation" are really few.