False-Name-Proof Recommendations in Social Networks

We study the problem of finding a recommendation for an uninformed user in a social network by weighting and aggregating the opinions offered by the informed users in the network. In social networks, an informed user may try to manipulate the recommendation by performing a false-name manipulation, wherein the user submits multiple opinions through fake accounts. To that end, we impose a no harm axiom: false-name manipulations by a user should not reduce the weight of other users in the network. We show that this axiom has deep connections to false-name-proofness. While it is impossible to design a mechanism that is best for every network subject to this axiom, we propose an intuitive mechanism LEGIT+, and show that it is uniquely optimized for small networks. Using real-world datasets, we show that our mechanism performs very well compared to two baseline mechanisms in a number of metrics, even on large networks.

[1]  A Thesis,et al.  An analysis of various tools, methods and systems to generate fake accounts for social media , 2014 .

[2]  J. Hopcroft,et al.  Algorithm 447: efficient algorithms for graph manipulation , 1973, CACM.

[3]  Vincent Conitzer,et al.  Worst-case efficiency ratio in false-name-proof combinatorial auction mechanisms , 2010, AAMAS.

[4]  Hervé Moulin,et al.  Fair division and collective welfare , 2003 .

[5]  A. Sen,et al.  Collective Choice and Social Welfare , 2017 .

[6]  Vincent Conitzer,et al.  False-Name-Proofness in Social Networks , 2010, WINE.

[7]  Makoto Yokoo,et al.  Characterizing false-name-proof allocation rules in combinatorial auctions , 2009, AAMAS.

[8]  H. Moulin.  Axioms of Cooperative Decision Making , 1988 .

[9]  Ariel D. Procaccia,et al.  Leximin Allocations in the Real World , 2015, EC.

[10]  Sylvain Bouveret,et al.  Computing leximin-optimal solutions in constraint networks , 2009, Artif. Intell..

[11]  Makoto Yokoo,et al.  The effect of false-name bids in combinatorial auctions: new fraud in internet auctions , 2004, Games Econ. Behav..

[12]  Ariel D. Procaccia,et al.  Truth, justice, and cake cutting , 2010, Games Econ. Behav..

[13]  Jérôme Kunegis,et al.  KONECT: the Koblenz network collection , 2013, WWW.

[14]  Alvin E. Roth,et al.  Pairwise Kidney Exchange , 2004, J. Econ. Theory.

[15]  Bracha Shapira,et al.  Recommender Systems Handbook , 2015, Springer US.

[16]  Brahim Bensaou,et al.  On max-min fairness and scheduling in wireless ad-hoc networks: analytical framework and implementation , 2001, MobiHoc '01.

[17]  Makoto Yokoo,et al.  False-name-proof mechanism design without money , 2011, AAMAS.

[18]  Salvador Barberà,et al.  Voting by Committees , 1991 .

[19]  Makoto Yokoo,et al.  Robust Combinatorial Auction Protocol against False-Name Bids , 2000, AAAI/IAAI.

[20]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[21]  Benjamin Hindman,et al.  Dominant Resource Fairness: Fair Allocation of Multiple Resource Types , 2011, NSDI.

[22]  Vincent Conitzer,et al.  Optimal False-Name-Proof Voting Rules with Costly Voting , 2008, AAAI.

[23]  Vincent Conitzer,et al.  False-name-proof matching , 2013, AAMAS.

[24]  Wesley W. Chu,et al.  A Social Network-Based Recommender System (SNRS) , 2010, Data Mining for Social Network Data.

[25]  Makoto Yokoo,et al.  False-Name-Proofness in Facility Location Problem on the Real Line , 2010, WINE.

[26]  Michael J. Pazzani,et al.  Content-Based Recommendation Systems , 2007, The Adaptive Web.

[27]  M. Satterthwaite,et al.  Strategy-proofness and single-peakedness , 1976 .

[28]  H. Moulin,et al.  Axioms of Cooperative Decision Making. , 1990 .

[29]  James Bennett,et al.  The Netflix Prize , 2007 .

[30]  Jennifer Golbeck,et al.  Generating Predictive Movie Recommendations from Trust in Social Networks , 2006, iTrust.

[31]  H. Moulin.  On strategy-proofness and single peakedness , 1980 .

[32]  Gilles Villard,et al.  Solving sparse rational linear systems , 2006, ISSAC '06.

[33]  Vincent Conitzer,et al.  Anonymity-Proof Voting Rules , 2008, WINE.

[34]  Lior Rokach,et al.  Introduction to Recommender Systems Handbook , 2011, Recommender Systems Handbook.

[35]  Yoav Shoham,et al.  Fab: content-based, collaborative recommendation , 1997, CACM.

[36]  Adam Tauman Kalai,et al.  Trust-based recommendation systems: an axiomatic approach , 2008, WWW.

[37]  K. Menger.  Zur allgemeinen Kurventheorie , 1927 .

[38]  Kim C. Border,et al.  Straightforward Elections, Unanimity, and Phantom Voters , 1983 .