| 1. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
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Forming Networks of Strategic Agents with Desired Topologies
- 2012
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Ingår i: WINE 2012 - Proceedings of the 8th International Conference on Internet and Network Economics. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 9783642353109 ; , s. 504-511
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Konferensbidrag (refereegranskat)abstract
- Many networks such as social networks and organizational networks in global companies consist of self-interested agents. The topology of these networks often plays a crucial role in important tasks such as information diffusion and information extraction. Consequently, growing a stable network having a certain topology is of interest. Motivated by this, we study the following important problem: given a certain desired network topology, under what conditions would best response (link addition/deletion) strategies played by self-interested agents lead to formation of a stable network having that topology. We study this interesting reverse engineering problem by proposing a natural model of recursive network formation and a utility model that captures many key features. Based on this model, we analyze relevant network topologies and derive a set of sufficient conditions under which these topologies emerge as pairwise stable networks, wherein no node wants to delete any of its links and no two nodes would want to create a link between them.
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| 2. |
- Dhamal, Swapnil Vilas, 1988, et al.
(författare)
-
Scalable Preference Aggregation in Social Networks
- 2013
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Ingår i: HCOMP 2013 - Proceedings of the First AAAI Conference on Human Computation and Crowdsourcing. ; , s. 42-50
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Konferensbidrag (refereegranskat)abstract
- In social choice theory, preference aggregation refers to computing an aggregate preference over a set of alternatives given individual preferences of all the agents. In real-world scenarios, it may not be feasible to gather preferences from all the agents. Moreover, determining the aggregate preference is computationally intensive. In this paper, we show that the aggregate preference of the agents in a social network can be computed efficiently and with sufficient accuracy using preferences elicited from a small subset of critical nodes in the network. Our methodology uses a model developed based on real-world data obtained using a survey on human subjects, and exploits network structure and homophily of relationships. Our approach guarantees good performance for aggregation rules that satisfy a property which we call expected weak insensitivity. We demonstrate empirically that many practically relevant aggregation rules satisfy this property. We also show that two natural objective functions in this context satisfy certain properties, which makes our methodology attractive for scalable preference aggregation over large scale social networks. We conclude that our approach is superior to random polling while aggregating preferences related to individualistic metrics, whereas random polling is acceptable in the case of social metrics.
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