Scalable Preference Aggregation in Social Networks

Dhamal, Swapnil and Narahari, Y (2013) Scalable Preference Aggregation in Social Networks. In: The First AAAI Conference on Human Computation and Crowdsourcing (HCOMP 2013), November 6-9, 2013, Palm Springs, California, USA. (In Press)

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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.

Item Type:	Conference Paper
Publisher:	http://humancomputation.com
Additional Information:	The copyright for this article belongs to Association for the Advancement of Artificial Intelligence (AAAI).
Keywords:	Preference aggregation, Social networks, Homophily, Submodular function, Random polling, Node selection.
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	26 Sep 2013 05:42
Last Modified:	25 Oct 2013 14:44
URI:	http://eprints.iisc.ac.in/id/eprint/47463

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