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  1. Proceedings of the 5th ACM workshop on HotPlanet (HotPlanet '13)
  2. Metric convergence in social network sampling
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The 5th ACM hotplanet workshop keynote speaker: smartphones, crowds, and the cloud: population guided sensing systems
What's in a name?: decoding router interface names
Efficient social network data query processing on MapReduce
Lessons learned from the netsense smartphone study
Trace selection for improved WLAN monitoring
PIXS: programmable intelligence for cross-platform socialization
Information bazaar: a contextual evaluation
Internet atlas: a geographic database of the internet
Extrapolating sparse large-scale GPS traces for contact evaluation
It's tea time: do you know where your mug is?
A framework for monitoring and measuring a large-scale distributed system in real time
Metric convergence in social network sampling

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Metric convergence in social network sampling

Content Provider ACM Digital Library
Author Blenn, Norbert Doerr, Christian
Abstract While enabling new research questions and methodologies, the massive size of social media platforms also poses a significant issue for the analysis of these networks. In order to deal with this data volume, researchers typically turn to samples of these graph structures to conduct their analysis. This however raises the question about the representativeness of such limited crawls, and the amount of data necessary to come to stable predictions about the underlying systems. This paper analyzes the convergence of six commonly used topological metrics as a function of the crawling method and sample size used. We find that graph crawling methods drastically over- and underestimate network metrics, and that a non-trivial amount of data is needed to arrive at a stable estimate of the underlying network.
Starting Page 45
Ending Page 50
Page Count 6
File Format PDF
ISBN 9781450321778
DOI 10.1145/2491159.2491168
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-08-16
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Social network analysis Breadth-first-search bfs Data quality Depth-first-search dfs Metric convergence
Content Type Text
Resource Type Article
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