Efficient Sampling for Better OSN Data Provisioning release_5sarkvdukbaghebw7tuuyylwzy

by Nick Duffield, Balachander Krishnamurthy

Released as a article .

2016  

Abstract

Data concerning the users and usage of Online Social Networks (OSNs) has become available externally, from public resources (e.g., user profiles), participation in OSNs (e.g., establishing relationships and recording transactions such as user updates) and APIs of the OSN provider (such as the Twitter API). APIs let OSN providers monetize the release of data while helping control measurement load, e.g. by providing samples with different cost-granularity tradeoffs. To date, this approach has been more suited to releasing transactional data, with graphical data still being obtained by resource intensive methods such a graph crawling. In this paper, we propose a method for OSNs to provide samples of the user graph of tunable size, in non-intersecting increments, with sample selection that can be weighted to enhance accuracy when estimating different features of the graph.
In text/plain format

Archived Files and Locations

application/pdf  484.9 kB
file_xoerrfi2orahhj3nsrlrrslw7q
arxiv.org (repository)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article
Stage   submitted
Date   2016-12-14
Version   v1
Language   en ?
arXiv  1612.04666v1
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: 264eac22-0252-441f-befe-2ac936960ea2
API URL: JSON