Decoding Information Propagation in Social Networks
Delve into the intricacies of information propagation in social networks with a focus on challenges like collecting and decomposing graphs to give them physical meaning. Explore high-level concepts like constraint propagation and identifying highways within networks. Understand the macro structure components and the physical significance behind decomposing graphs in a directed acyclic graph system with millions of nodes. Uncover the complexities of the Twitter social graph, including the relationships and interactions between nodes. Join the exploration into the physical implications of decomposing large-scale networks for enhanced understanding.
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Presentation Transcript
Information propagation in social networks Maksym Gabielkov, Ashwin Rao, Arnaud Legout EPI DIANA, Sophia Antipolis {maksym.gabielkov, arnaud.legout}@inria.fr
Producer Consumers
Follow Relationship in Twitter Bob follows Alice Alice follows Bob Alice Bob
The Twitter Social Graph Alice Bob
+500 million nodes +24 billion edges Challenges 1. Collect the graph 2. Decompose the graph 3. Give a physical meaning to the decomposition
How is constraint information propagation? Identify the highways
1 1 1 1 1 1 4 1 3 3 4 1 1 1
1 1 1 1 1 1 4 1 3 3 4 1 1 1
Directed acyclic graph 249 million nodes Twitter social graph 500 million nodes
OUT-TENDRILS OTHER IN-TENDRILS BRIDGES LSC OUT IN DISCONNECTED
Directed acyclic graph 249 million nodes Twitter social graph 500 million nodes Macro structure 8 components
What is the physical meaning of decomposition?
1% accounts <0.01% edges <0.01% tweets
98% of the tweets 98% of the edges 50% of the accounts
1,5% of the tweets 5,3% of the accounts 0% outgoing edges
21,4% of the accounts 0,25% of the tweets
21,6% of the accounts 99% no edge 80% no tweet
Information propagation in social networks Maksym Gabielkov, Ashwin Rao, Arnaud Legout EPI DIANA, Sophia Antipolis {maksym.gabielkov, arnaud.legout}@inria.fr
Twitter in 2009 41.7 million users 1.47 billion follow links Average degree: 35 Partial crawls Twitter in 2012 537 million users 23.95 billion follow links Average degree: 44 Complete crawl
