Reaching Consensus on Social Networks

Research in sociology studies the effectiveness of social networks in achieving computational tasks. Typically the agents who are supposed to achieve a task are unaware of the underlying social network except their immediate friends. They have limited memory, communication, and coordination. These limitations result in computational obstacles in achieving otherwise trivial computational problems. One of the simplest problems studied in the social sciences involves reaching a consensus among players between two alternatives which are otherwise indistinguishable. In this paper we formalize the computational model of social networks. We then analyze the consensus problem as well as the problem of reaching a consensus which is identical to the majority of the original signals. In both models we seek to minimize the time it takes players to reach a consensus.

[1]  Jon M. Kleinberg,et al.  The structure of information pathways in a social communication network , 2008, KDD.

[2]  T. Liggett Interacting Particle Systems , 1985 .

[3]  Ramamohan Paturi,et al.  Good Edge, Bad Edge: How Network Structure Affects a Group's Ability to Coordinate , 2009 .

[4]  Land,et al.  No perfect two-state cellular automata for density classification exists. , 1995, Physical review letters.

[5]  Elchanan Mossel,et al.  Complete Convergence of Message Passing Algorithms for Some Satisfiability Problems , 2006, Theory Comput..

[6]  P. Clifford,et al.  A model for spatial conflict , 1973 .

[7]  M. Kearns,et al.  An Experimental Study of the Coloring Problem on Human Subject Networks , 2006, Science.

[8]  Johannes Gehrke,et al.  Gossip-based computation of aggregate information , 2003, 44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings..

[9]  Alexandros G. Dimakis,et al.  Reaching consensus about gossip : convergence times and costs , 2008 .

[10]  Martin Vetterli,et al.  Interval consensus: From quantized gossip to voting , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[11]  J. Stephen Judd,et al.  Behavioral experiments on biased voting in networks , 2009, Proceedings of the National Academy of Sciences.

[12]  R. Holley,et al.  Ergodic Theorems for Weakly Interacting Infinite Systems and the Voter Model , 1975 .

[13]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[14]  Leslie G. Valiant,et al.  Evolvability , 2009, JACM.

[15]  B. Latané,et al.  Spatial clustering in the conformity game: Dynamic social impact in electronic groups. , 1996 .

[16]  A-L Barabási,et al.  Structure and tie strengths in mobile communication networks , 2006, Proceedings of the National Academy of Sciences.

[17]  Michael Kearns,et al.  Biased Voting and the Democratic Primary Problem , 2008, WINE.