552241
Opinion Dynamics and Wisdom under Conformity
We present a model of opinion formation where individuals repeatedly engage in discussion and update their opinion in a social network similarly to the DeGroot model. Abstracting from the standard assumption that individuals always report their opinion truthfully, agents in our model may state an opinion that differs from their true opinion. The incentive to do so is induced by agents' preferences for conformity. We model opinion formation as a dynamic process and identify conditions for convergence to a consensus. Studying the consensus in detail, we show that an agent's social influence on the consensus opinion is increasing in network centrality and decreasing in the level of conformity. Thus, lower conformity fosters opinion leadership. Moreover, assuming that the initial opinion is a noisy signal about some true state of the world, we study how conformity affects the efficiency of information aggregation or the ``wisdom'' of the society. We show that the society becomes wiser, in the sense of a smaller mean squared error of their estimate, if players who are well informed (relative to their network importance) are less conform, while uninformed players (relative to their network importance) conform more with their neighbors.
120637488
Factoring and weighting approaches to status scores and clique identification
(1972). Factoring and weighting approaches to status scores and clique identification. The Journal of Mathematical Sociology: Vol. 2, No. 1, pp. 113-120.
144889829
Theoretical Foundations for Centrality Measures
Three measures of actors' network centrality are derived from an elementary rocess model of social influence. The measures are closely related to, and cast new light on, widely used measures of actors' centrality; for example, the essential social organization of status that has been assumed by Hubbell, Bonacich, Coleman, and Burt appears as a deducible outcome of this social influence process. Unlike previous measures, which have been viewed as competing alternatives, the present measures are complementary and, in their juxtaposition, provide for a rich description of social structure. The complementary indicates a degree of theoretical unification in the work on network centrality that was heretofore unsuspected.
151860479
Persuasion Bias, Social Influence, and Unidimensional Opinions
We propose a boundedly rational model of opinion formation in which individuals are subject to persuasion bias; that is, they fail to account for possible repetition in the information they receive. We show that persuasion bias implies the phenomenon of social influence, whereby one's influence on group opinions depends not only on accuracy, but also on how well-connected one is in the social network that determines communication. Persuasion bias also implies the phenomenon of unidimensional opinions; that is, individuals' opinions over a multidimensional set of issues converge to a single "left-right" spectrum. We explore the implications of our model in several natural settings, including political science and marketing, and we obtain a number of novel empirical implications.
7824258
Naïve Learning in Social Networks and the Wisdom of Crowds
We study learning in a setting where agents receive independent noisy signals about the true value of a variable and then communicate in a network. They naively update beliefs by repeatedly taking weighted averages of neighbors' opinions. We show that all opinions in a large society converge to the truth if and only if the influence of the most influential agent vanishes as the society grows. We also identify obstructions to this, including prominent groups, and provide structural conditions on the network ensuring efficient learning. Whether agents converge to the truth is unrelated to how quickly consensus is approached. (JEL D83, D85, Z13)
35785090
A study of normative and informational social influences upon individual judgement.
Several modifications of the Asch experiment in which the S judges the length of lines in the company of a group of “stooges” who carry out the experimenter's instructions are described. These include a face-to-face situation, an anonymous situation, and a group situation, with self-commitment, publ
145653053
An Experimental Investigation of Why Individuals Conform
Social interdependence is believed to play an important role in individual choice behavior. I first outline a simple model constructed on the premise that people are motivated by their own payoff and by how their action compares to others in their reference group. I show that conformity in actions may arise from learning about the descriptive norm, or from image-related concerns. In order to empirically disentangle the two, I use the fact that image-related concerns can only be present if actions are publicly observable. The model predictions are then tested in a charitable contribution experiment in which the actions and identities of the subjects are unmasked in a controlled and systematic way. Both learning about the descriptive norm (i.e., what others are doing) and image-related concerns play an important role in the choices of the subjects. Individuals indulge in social comparison and change their contributions in the direction of the social norm even when their identities are hidden. Once identities and contribution distributions of group members are revealed, individuals conform to the choice of other group members. Moreover, I find that social ties (defined as subjects knowing each other from outside the lab) affect the role of social influence: Subjects only respond to the choices of group members they are friends with. In particular, a low contribution norm evolves that causes individuals to contribute less in the presence of friends. This suggests that social comparison and image-related concerns may not always lead to higher contributions.
154678438
A Theory of Conformity
This paper analyzes a model of social interaction in which individuals care about status as well as "intrinsic" utility (which refers to utility derived directly from consumption). Status is assumed to depend on public perceptions about an individual's predispositions rather than on the individual's actions. However, since predispositions are unobservable, actions signal predispositions and therefore affect status. When status is sufficiently important relative to intrinsic utility, many individuals conform to a single, homogeneous standard of behavior, despite heterogeneous underlying preferences. They are willing to conform because they recognize that even small departures from the social norm will seriously impair their status. The fact that society harshly censures all nonconformists is not simply assumed (indeed, status varies smoothly with perceived type); rather, it is produced endogenously. Despite this penalty, agents with sufficiently extreme preferences refuse to conform. The model provides an explanation for the fact that standards of behavior govern some activities but do not govern others. It also suggests a theory of how standards of behavior might evolve in response to changes in the distribution of intrinsic preferences. In particular, for some values of the preference parameters, norms are both persistent and widely followed; for other values, norms are transitory and confined to small groups. Thus the model produces both customs and fads. Finally, an extension of the model suggests an explanation for the development of multiple subcultures, each with its own distinct norm.
15827429
TESTING MODELS OF SOCIAL LEARNING ON NETWORKS : EVIDENCE FROM A FRAMED FIELD EXPERIMENT
Theory has focused on two leading models of social learning on networks: Bayesian and DeGroot rules of thumb learning. These models can yield greatly divergent behavior; individuals employing rules of thumb often double-count information and may not exhibit convergent behavior in the long run. By conducting a unique lab experiment in rural Karnataka, India, set up to exactly differentiate between these two models, we test which model best describes social learning processes on networks. We study experiments in which seven individuals are placed into a network, each with full knowledge of its structure. The participants attempt to learn the underlying (binary) state of the world. Individuals receive independent, identically distributed signals about the state in the first period only; thereafter, individuals make guesses about the underlying state of the world and these guesses are transmitted to their neighbors at the beginning of the following round. We consider various environments including incomplete information Bayesian models and provide evidence that individuals are best described by DeGroot models wherein they either take simple majority of opinions in their neighborhood.
146226028
Boundedly Rational Opinion Dynamics in Directed Social Networks: Theory and Experimental Evidence
This paper investigates opinion dynamics and social influence in directed communication networks. We study the properties of a generalized boundedly rational model of opinion formation in which individuals aggregate the information they receive by using weights that are a function of their neighbors' indegree. We then present an experiment designed to test the predictions of the model. We find that both Bayesian updating and boundedly rational updating a la DeMarzo et al. (2003) are rejected by the data. Consistent with our theoretical predictions, the social influence of an agent is positively and significantly affected by the number of individuals she listens to. When forming their opinions, agents do take into account the structure of the communication network, although in a sub-optimal way.
5681020
Bayesian learning in social networks
Abstract We extend the standard model of social learning in two ways. First, we introduce a social network and assume that agents can only observe the actions of agents to whom they are connected by this network. Secondly, we allow agents to choose a different action at each date. If the network satisfies a connectedness assumption, the initial diversity resulting from diverse private information is eventually replaced by uniformity of actions, though not necessarily of beliefs, in finite time with probability one. We look at particular networks to illustrate the impact of network architecture on speed of convergence and the optimality of absorbing states. Convergence is remarkably rapid, so that asymptotic results are a good approximation even in the medium run.
12751942
Public Disagreement
Members of di¤erent social groups often hold widely divergent public beliefs regarding the nature of the world in which they live. We develop a model that can accommodate such public disagreement, and use it to explore questions concerning the aggregation of distributed information and the consequences of social integration. The model involves heterogeneous priors, private information, and repeated communication until beliefs become public information. We show that when priors are correlated, all private information is eventually aggregated and public beliefs are identical to those arising under observable priors. When priors are independently distributed, however, some private information is never revealed and the expected value of public disagreement is greater when priors are unobservable than when they are observable. If the number of individuals is large, communication breaks down entirely in the sense that disagreement in public beliefs is approximately equal to disagreement in prior beliefs. Interpreting integration in terms of the observability of priors, we show how increases in social integration can give rise to less divergent public beliefs on average. We thank the Institute for Advanced Study for nancial support and hospitality, and Danielle Allen, Roland Benabou, Sylvain Chassang, Glenn Loury, Eric Maskin, Debraj Ray, and seminar participants at IAS, ISI, NYU, Princeton, Rutgers and the University of Illinois at Urbana-Champaign for helpful comments. yDepartment of Economics, Barnard College, Columbia University and the Institute for Advanced Study (rs328@columbia.edu) zDepartment of Economics, MIT and the Institute for Advanced Study (myildiz@mit.edu)
14414203
Pathological Outcomes of Observational Learning
This paper systematically analyzes and enriches the observational learning paradigm of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992).
8301131
Spread of (mis)information in social networks
We provide a model to investigate the tension between information aggregation and spread of misinformation in large societies (conceptualized as networks of agents communicating with each other). Each individual holds a belief represented by a scalar. Individuals meet pairwise and exchange information, which is modeled as both individuals adopting the average of their pre-meeting beliefs. When all individuals engage in this type of information exchange, the society will be able to effectively aggregate the initial information held by all individuals. There is also the possibility of misinformation, however, because some of the individuals are “forceful,” meaning that they influence the beliefs of (some) of the other individuals they meet, but do not change their own opinions. The paper characterizes how the presence of forceful agents interferes with information aggregation. Under the assumption that even forceful agents obtain some information (however infrequent) from some others (and additional weak regularity conditions), we first show that beliefs in this class of societies converge to a consensus among all individuals. This consensus value is a random variable, however, and we characterize its behavior. Our main results quantify the extent of misinformation in the society by either providing bounds or exact results (in some special cases) on how far the consensus value can be from the benchmark without forceful agents (where there is efficient information aggregation). The worst outcomes obtain when there are several forceful agents and forceful agents themselves update their beliefs only on the basis of information they obtain from individuals most likely to have received their own information previously.
144197299
Characteristics of the Opinion Leader: A New Dimension
Abstract This study empirically examined the role of a personality trait, public individuation, in furthering our understanding of opinion leadership. Relevance of this new psychological dimension, and past findings on characteristics of opinion leaders are discussed. Discriminant analysis revealed that, in addition to personal involvement and product familiarity, public individuation was the only other variable which was important in distinguishing opinion leaders from non-leaders. Risk preference, open-mindedness, and mass media exposure, though correlated with opinion leadership, were not found to be important predictors of opinion leadership. Implications for advertisers are discussed.
153974328
Social Structure and Institutional Design: Evidence from a Lab Experiment in the Field
In settings with poor formal contract enforcement, profitable investments are likely unrealized. While social closeness can mitigate contractual incompleteness, we examine how to improve the preponderance of cases where contracting parties cannot rely upon social ties. We ask if a community can enlist members to monitor transactions or punish offending parties. We conduct a laboratory experiment in 40 Indian villages, with 960 non-anonymized subjects, where we have social network data. Participants play modified sender-receiver investment games, with and without third-party monitors and punishers. We examine whether network centrality of the third party increases efficiency of interaction. Furthermore, we decompose the efficiency increase into a monitoring channel (central third parties are valuable since they may influence reputations) and an enforcement channel (central third parties may be more able to punish without fear of retaliation). Assigning a third party at the 75th percentile of the centrality distribution (as compared to the 25th) increases efficiency by 21% relative to the mean: we attribute 2/5 of the effect to monitoring and 3/5 to enforcement. The largest efficiency increase occurs when senders and receivers are socially distant, unable to maintain efficient levels autonomously. Results cannot be explained by demographics such as elite status, caste, wealth or gender. Our findings show not every member is equally well-equipped to be part of a local institution. Knowing that a central third party observes their interaction increases sender-receiver efficiency. More importantly, to be able to punish someone, the third party must be important in the community.
34354751
Trust, influence, and convergence of behavior in social networks
I propose a social learning framework where agents repeatedly take the weighted average of all agents' current opinions in forming their own for the next period. They also update the influence weights that they place on each other. It is proven that both opinions and the influence weights are convergent. In the steady state, opinions reach consensus and influence weights are distributed evenly. Convergence occurs with an extended model as well, which indicates the tremendous influential power possessed by a minority group. Computer simulations of the updating processes provide supportive evidence.
144839904
A formal theory of social power
This paper builds on French's (1956) Formal Theory of Social Power. In the theory, a population's power structure is formally related to its structure of influential communications which, in turn, is formally related to its pattern and prevalence of interpersonal agreements. The theory's predictions include the following about the members of a population: (1) the expected influence of each member in determining other members’ opinions on an issue; (2) the probability of consensus on an issue in the population or in any given subset (dyad or cluster) of the members; and (3) the probability that any given proportion of the members (e.g., a majority) will be in agreement on an issue. The theory overcomes well‐recognized limitations of French's seminal effort. Its predictions rest (1) on a micro‐level process of opinion change and (2) on macro‐level variations in the pattern and strengths of the ties that comprise a power structure.
121587691
Social influence and opinions
In this paper we describe an approach to the relationship between a network of interpersonal influences and the content of individuals’ opinions. Our work starts with the specification of social pr...
17438004
Information Heterogeneity and the Speed of Learning in Social Networks
This paper examines how the structure of a social network and the quality of information available to different agents determine the speed of social learning. To this end, we study a variant of the seminal model of DeGroot (1974), according to which agents linearly combine their personal experiences with the views of their neighbors. We show that the rate of learning has a simple analytical characterization in terms of the relative entropy of agents’ signal structures and their eigenvector centralities. Our characterization establishes that the way information is dispersed throughout the social network has non-trivial implications for the rate of learning. In particular, we show that when the informativeness of different agents’ signal structures are comparable in the sense of Blackwell (1953), then a positive assortative matching of signal qualities and eigenvector centralities maximizes the rate of learning. On the other hand, if information structures are such that each individual possesses some information crucial for learning, then the rate of learning is higher when agents with the best signals are located at the periphery of the network. Finally, we show that the extent of asymmetry in the structure of the social network plays a key role in the long-run dynamics of the beliefs.
18520288
A stabilization theorem for dynamics of continuous opinions
A stabilization theorem for processes of opinion dynamics is presented. The theorem is applicable to a wide class of models of continuous opinion dynamics based on averaging (like the models of Hegselmann–Krause and Weisbuch–Deffuant). The analysis detects self-confidence as a driving force of stabilization.
8130429
Opinion dynamics and bounded confidence: models, analysis and simulation
When does opinion formation within an interacting group lead to consensus, polarization or fragmentation? The article investigates various models for the dynamics of continuous opinions by analytical methods as well as by computer simulations. Section 2 develops within a unified framework the classical model of consensus formation, the variant of this model due to Friedkin and Johnsen, a time-dependent version and a nonlinear version with bounded confidence of the agents. Section 3 presents for all these models major analytical results. Section 4 gives an extensive exploration of the nonlinear model with bounded confidence by a series of computer simulations. An appendix supplies needed mathematical definitions, tools, and theorems.
145447931
WHEN WILL THEY EVER MAKE UP THEIR MINDS? THE SOCIAL STRUCTURE OF UNSTABLE DECISION MAKING
French (1977), Harary (1959), and Abelson (1964) initiated a prominent line of social influence models to explain social norms or collective decisions from the structure of influence networks. These models fail to generate unstable decision dynamics, a phenomenon that can be observed in collective decision-making. To capture instability, we assume that decision-makers raise their level of salience to reduce expected losses from decision-outcomes. Our model generates persistently unstable outcome patterns under conditions related to the social network and to intolerance for expected losses. A 6-actor example reveals stable outcomes for low intolerance, complex oscillations for intermediate levels of intolerance, and simple and regular oscillation for high intolerance. We discuss implications for the predictability of collective decision-making.
3497610
The dynamics of continuous cultural traits in social networks
We consider an overlapping generations model where continuous cultural traits are transmitted from an adult generation to the children. A weighted social network describes how children are influenced not only by their parents but also by other role models within the society. Parents can invest into the purposeful socialization of their children by strategically displaying a cultural trait (which need not coincide with their true cultural trait). We observe a cultural substitution effect when parents choose their behavior optimally. Based on Nash equilibrium behavior, we then study the dynamics of cultural traits throughout generations. These converge if parent's influence on their children is large enough compared to the social environment's influence. Under convergent dynamics, closed subgroups fully assimilate, while heterogeneous traits prevail in the other groups. Speed of convergence is low when parents' incentives to socialize their children to the own trait are high.
154778200
Influencing the influencers: a theory of strategic diffusion
The growth of the Internet and assorted technologies has made it possible to collect and process detailed information on social networks. This article investigates how firms (and governments) can harness the power of social networks to promote their goals. We show that the optimal use of social networks leads to higher sales and greater profits. However, an increase in the level and dispersion of social interaction can increase or decrease the optimal influence strategy and profits of the player, depending on the content of the interaction. Optimal influence strategies will target individuals with low or high connections, depending on the content of interaction. Finally, the returns to investing in market research on social networks are greater in more unequal networks.
53319463
Reaching consensus on rumors
An important contribution in sociophysics is the Galam’s model of rumors spreading. This model provides an explanation of rumors spreading in a population and explains some interesting social phenomena such as the diffusion of hoaxes. In this paper the model has been reformulated as a Markov process highlighting the stochastic nature of the phenomena. This formalization allows us to derive conditions for consensus to be reached and for the existence of some interesting phenomena such as the emergence of impasses. The proposed formulation allows a deeper and more comprehensive analysis of the diffusion of rumors.
15532545
Informational externalities and emergence of consensus
We study a general model of dynamic games with purely informational externalities. We prove that eventually all motives for experimentation disappear, and provide the exact rate at which experimentation decays. We also provide tight conditions under which players eventually reach a consensus. These results imply extensions of many known results in the literature of social learning and getting to agreement.
144085247
Social Identifications: A Social Psychology of Intergroup Relations and Group Processes
Foreward. Preface. 1. Introduction 2. The social identity approach: context and content 3. Intergroup behaviour 4. From stereotyping to ideology 5. Intragroup behaviour: Processes within the groups 6. Social presence and social performance 7. Collective behaviour 8. Conformity and social influence 9. Language, speech, and communication 10. Conclusions References. Author index. Subject index.
120077293
Reaching a Consensus
Abstract Consider a group of individuals who must act together as a team or committee, and suppose that each individual in the group has his own subjective probability distribution for the unknown value of some parameter. A model is presented which describes how the group might reach agreement on a common subjective probability distribution for the parameter by pooling their individual opinions. The process leading to the consensus is explicitly described and the common distribution that is reached is explicitly determined. The model can also be applied to problems of reaching a consensus when the opinion of each member of the group is represented simply as a point estimate of the parameter rather than as a probability distribution.
59455732
The wisdom of crowds in one mind: How individuals can simulate the knowledge of diverse societies to reach better decisions
The joint knowledge of many diverse individuals can outperform experts in estimation and decision-making problems. This wisdom of the crowd has been demonstrated in different societal areas such as internet search engines, political elections or stock markets. Recently, psychologists argued that humans may even simulate a diverse society in their own minds by drawing different answers from their brain (Vul & Pashler, 2008). The underlying idea is that individuals can access different knowledge areas in their brain, whose joint evaluation yields better estimates than their separate consideration. This article presents a mathematical treatment of the wisdom of crowds and two potential mechanisms to quantify the wisdom of crowds in one mind. The implications of both methods are analyzed and applied to new experimental data (N=144)(N=144), which contain five consecutive estimates from the same individuals. The theoretical and empirical analysis demonstrates limitations of the wisdom of crowds in one mind: Asking oneself several times is on average less powerful than asking only one other individual. This is due to the smaller diversity of estimates of similar individuals and the larger average bias to which they converge. Further, individuals cannot perform independent draws from an “internal distribution”. Hence, there may be other mechanisms at work such as talking oneself into believing initial guesses or eliciting progressively wilder ones.