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  1. Proceedings of the 2013 SIGMOD/PODS Ph.D. symposium (SIGMOD'13 PhD Symposium)
  2. Information diffusion in online social networks
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Exploiting in-network processing for big data management
Learning queries for relational, semi-structured, and graph databases
Exploratory mining of collaborative social content
DeepSea: self-adaptive data partitioning and replication in scalable distributed data systems
Turning scientists into data explorers
Discovering and disambiguating named entities in text
Designing a database system for modern processing architectures
Information diffusion in online social networks
The tantalizing new prospect of index-based diversified retrieval
Effective hashing for large-scale multimedia search
Efficient and scalable monitoring and summarization of large probabilistic data
RDF-4G: algorithmic building blocks for large-scale graph analytics

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Information diffusion in online social networks

Content Provider ACM Digital Library
Author Guille, Adrien
Abstract Online social networks play a major role in the spread of information at very large scale and it becomes essential to provide means to analyze this phenomenon. Analyzing information diffusion proves to be a challenging task since the raw data produced by users of these networks are a flood of ideas, recommendations, opinions, etc. The aim of this PhD work is to help in the understanding of this phenomenon. So far, our contributions are the following: (i) a survey of developments in the field; (ii) T-BaSIC, a graph-based model for information diffusion prediction; (iii) SONDY, an open source platform that helps understanding social network users' interests and activity by providing emerging topics and events detection as well as network analysis functionalities.
Starting Page 31
Ending Page 36
Page Count 6
File Format PDF
ISBN 9781450321556
DOI 10.1145/2483574.2483575
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2013-06-23
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Information diffusion Online social networks
Content Type Text
Resource Type Article
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