Noise, bias, and expertise in political communication networks

Abstract A central focus in the study of social networks and politics centers on the dynamics of diffusion and persuasion, as well as the manner in which these processes are affected by expert “opinion leaders.” The role of experts is particularly important in communication processes characterized by noisy, biased information – processes in which people with variable levels of expertise and strength of preference select informants, as well as being influenced by them. We employ an experimental approach that addresses these problems at multiple levels of observation in a highly dynamic context – small groups of individuals communicating with one another in real time. The analysis shows that participants formulate candidate judgments that decay in time, but the decay occurs at a significantly lower rate among the better informed. Moreover, the better informed are less affected by socially communicated messages regarding the candidates. Hence the influence of experts is not only due to their powers of persuasion, but also to the durability of their own privately formulated opinions. Their role in the communication process is further heightened by the higher value placed by participants on expert opinion, which in turn exposes the recipient to a heterogeneous and hence potentially influential stream of information.

[1]  D. Lazer,et al.  The Coevolution of Networks and Political Attitudes , 2010 .

[2]  L. Festinger,et al.  A Theory of Cognitive Dissonance , 2017 .

[3]  Z. Kunda,et al.  Social Cognition: Making Sense of People , 1999 .

[4]  M. Lodge,et al.  The Responsive Voter: Campaign Information and the Dynamics of Candidate Evaluation , 1995, American Political Science Review.

[5]  R L Williams,et al.  A Note on Robust Variance Estimation for Cluster‐Correlated Data , 2000, Biometrics.

[6]  John Ryan,et al.  Communication, Influence, and Informational Asymmetries among Voters: Communication and Informational Asymmetries , 2010 .

[7]  Russell H. Fazio,et al.  Attitudes as object-evaluation associations: Determinants, consequences, and correlates of attitude accessibility. , 1995 .

[8]  P. Lazarsfeld,et al.  6. Katz, E. Personal Influence: The Part Played by People in the Flow of Mass Communications , 1956 .

[9]  Sidney Verba,et al.  Small Groups and Political Behavior-A Study of Leadership. , 1961 .

[10]  Timothy C. Salmon,et al.  Coming and going: Experiments on endogenous group sizes for excludable public goods , 2009 .

[11]  Cheryl Boudreau,et al.  Closing the Gap: When Do Cues Eliminate Differences between Sophisticated and Unsophisticated Citizens? , 2009, The Journal of Politics.

[12]  R. Huckfeldt,et al.  Citizens, Politics and Social Communication: Information and Influence in an Election Campaign , 1995 .

[13]  John G. Bullock Partisan Bias and the Bayesian Ideal in the Study of Public Opinion , 2009, The Journal of Politics.

[14]  Penny S. Visser,et al.  Social network composition and attitude strength: Exploring the dynamics within newly formed social networks , 2009 .

[15]  Joseph Bafumi,et al.  A New Partisan Voter , 2009, The Journal of Politics.

[16]  John Ryan,et al.  Communication, Influence, and Informational Asymmetries Among Voters , 2008 .

[17]  A. Downs An Economic Theory of Democracy , 1957 .

[18]  Mathew D. McCubbins,et al.  The Democratic Dilemma: Can Citizens Learn What They Need to Know? , 1998 .

[19]  E. Fehr,et al.  Altruistic punishment in humans , 2002, Nature.

[20]  John Ryan,et al.  Social Networks as a Shortcut to Correct Voting , 2011 .

[21]  Larry M. Bartels Beyond the Running Tally: Partisan Bias in Political Perceptions , 2002 .

[22]  P. Lazarsfeld,et al.  Voting: A Study of Opinion Formation in a Presidential Campaign , 1954 .

[23]  Peter C. Ordeshook,et al.  Information, Electoral Equilibria, and the Democratic Ideal , 1986, The Journal of Politics.

[24]  D. Green,et al.  MISPERCEPTIONS ABOUT PERCEPTUAL BIAS , 1999 .

[25]  Robert Huckfeldt,et al.  Moths, Flames, and Political Engagement: Managing Disagreement within Communication Networks , 2008, The Journal of Politics.

[26]  Jeffrey Levine,et al.  The Dynamics of Collective Deliberation in the 1996 Election: Campaign Effects on Accessibility, Certainty, and Accuracy , 2000, American Political Science Review.

[27]  Robert Huckfeldt,et al.  Social Contexts, Social Networks, and Urban Neighborhoods: Environmental Constraints on Friendship Choice , 1983, American Journal of Sociology.

[28]  Robert Huckfeldt,et al.  The Social Communication of Political Expertise , 2001 .

[29]  U. Fischbacher z-Tree: Zurich toolbox for ready-made economic experiments , 1999 .

[30]  Mark S. Granovetter The Strength of Weak Ties , 1973, American Journal of Sociology.

[31]  E. Ostrom,et al.  Covenants with and without a Sword: Self-Governance Is Possible , 1992, American Political Science Review.

[32]  W. Rogers Regression standard errors in clustered samples , 1994 .

[33]  E. Katz The Two-Step Flow of Communication: An Up-To-Date Report on an Hypothesis , 1957 .

[34]  Charles S. Taber,et al.  Elements of Reason: Three Steps toward a Theory of Motivated Political Reasoning , 2000 .

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