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ForestStream: Accurate Measurement of Cascades in Online Social Networks

Title
ForestStream: Accurate Measurement of Cascades in Online Social Networks
Author
한진영
Keywords
Memory management; Facebook, Vegetation; Sampling methods; Receivers; Estimation
Issue Date
2017-07
Publisher
IEEE
Citation
2017 26th International Conference on Computer Communication and Networks (ICCCN), Page. 1-9
Abstract
Various Online Social Network (OSN) based applications depend on the interactions between users to disseminate information and recruit more users. The temporal evolution of adoption or cascade process of new products, applications or ideas is important to advertisers, OSN operators and application developers. Interactions between users are represented by massive directed graphs, so graph sampling methods were proposed to capture their properties. Existing graph sampling methods, such as a simple random walk, however, are ill- suited for capturing this and other dynamic properties of the graph. We propose ForestStream, a measurement method that relies on a combination of sampling and streaming with the goal of capturing the statistical properties of cascades in OSN graphs. We demonstrate our method's accuracy over existing methods in inferring the cascade statistics, with a low memory usage.
URI
https://ieeexplore.ieee.org/document/8038387/http://repository.hanyang.ac.kr/handle/20.500.11754/103454
ISBN
978-1-5090-2991-4
DOI
10.1109/ICCCN.2017.8038387
Appears in Collections:
COLLEGE OF COMPUTING[E] > MEDIA, CULTURE, AND DESIGN TECHNOLOGY(ICT융합학부) > Articles
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