AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Robust incentive techniques for peer-to-peer networks
EC '04 Proceedings of the 5th ACM conference on Electronic commerce
FOCS '05 Proceedings of the 46th Annual IEEE Symposium on Foundations of Computer Science
Searching for expertise in social networks: a simulation of potential strategies
GROUP '05 Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work
Analysis of topological characteristics of huge online social networking services
Proceedings of the 16th international conference on World Wide Web
On threshold behavior in query incentive networks
Proceedings of the 8th ACM conference on Electronic commerce
Measurement and analysis of online social networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
An incentive mechanism for message relaying in unstructured peer-to-peer systems
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Power-Law Distributions in Empirical Data
SIAM Review
Modelling user participation in organisations as networks
Expert Systems with Applications: An International Journal
Finding red balloons with split contracts: robustness to individuals' selfishness
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Sybil-proof mechanisms in query incentive networks
Proceedings of the fourteenth ACM conference on Electronic commerce
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The advent of large scale online social networks has resulted in a spurt of studies on the user participation in the networks. We consider a query incentive model on social networks, where user's queries are answered through her friendship network and there are `rewards' or `incentives' in the system to answer the queries utilizing ones community. We model the friendship network as a random graph with power-law degree distribution, and show that the reward function exhibits a theoretic threshold behavior on the scaling exponent α, a network parameter. Specifically, there exists a threshold on α above which the reward is exponential in the average path length in the network and below the threshold, the reward is proportional to the average path length. We demonstrate this finding on simulated power-law networks and real world data gathered from online social media such as Flickr, Digg, YouTube and Yahoo! Answers.