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Social influence and the collective dynamics of opinion formation.

Moussaïd M, Kämmer JE, Analytis PP, Neth H - PLoS ONE (2013)

Bottom Line: A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions.In particular, we identify two major attractors of opinion: (i) the expert effect, induced by the presence of a highly confident individual in the group, and (ii) the majority effect, caused by the presence of a critical mass of laypeople sharing similar opinions.These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.

View Article: PubMed Central - PubMed

Affiliation: Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, Germany.

ABSTRACT
Social influence is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. In our strongly interconnected society, social influence plays a prominent role in many self-organized phenomena such as herding in cultural markets, the spread of ideas and innovations, and the amplification of fears during epidemics. Yet, the mechanisms of opinion formation remain poorly understood, and existing physics-based models lack systematic empirical validation. Here, we report two controlled experiments showing how participants answering factual questions revise their initial judgments after being exposed to the opinion and confidence level of others. Based on the observation of 59 experimental subjects exposed to peer-opinion for 15 different items, we draw an influence map that describes the strength of peer influence during interactions. A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions. In particular, we identify two major attractors of opinion: (i) the expert effect, induced by the presence of a highly confident individual in the group, and (ii) the majority effect, caused by the presence of a critical mass of laypeople sharing similar opinions. Additional simulations reveal the existence of a tipping point at which one attractor will dominate over the other, driving collective opinion in a given direction. These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.

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Which attractor dominates when the majority effect and the expert effect apply simultaneously?(A) The evolution of collective opinion when varying the relative proportion of experts pExp, holding an opinion Oexp and a high confidence level Cexp = 6, and the proportion of people in the majority group pmaj holding an opinion Omaj and a low confidence level randomly chosen in the interval Cmaj = [1 3]. Here, the number of neutral individuals is fixed to pNeut = 0. (B) Phase diagram showing the parameter space where the majority or the expert effects applies, when increasing the proportion of neutral individuals pNeut holding a random opinion and a low confidence level randomly chosen in the interval Cuni = [1 3]. The schematic regions delimited by black or white dashed lines show the zones where the collective opinion converges toward the majority or the expert opinion, respectively. In the transition zone, the collective opinion converges somewhere between Oexp and Omaj. In some rare cases, the crowd splits into two groups or more.
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pone-0078433-g006: Which attractor dominates when the majority effect and the expert effect apply simultaneously?(A) The evolution of collective opinion when varying the relative proportion of experts pExp, holding an opinion Oexp and a high confidence level Cexp = 6, and the proportion of people in the majority group pmaj holding an opinion Omaj and a low confidence level randomly chosen in the interval Cmaj = [1 3]. Here, the number of neutral individuals is fixed to pNeut = 0. (B) Phase diagram showing the parameter space where the majority or the expert effects applies, when increasing the proportion of neutral individuals pNeut holding a random opinion and a low confidence level randomly chosen in the interval Cuni = [1 3]. The schematic regions delimited by black or white dashed lines show the zones where the collective opinion converges toward the majority or the expert opinion, respectively. In the transition zone, the collective opinion converges somewhere between Oexp and Omaj. In some rare cases, the crowd splits into two groups or more.

Mentions: Our simulations show that the majority effect and the expert effect are not systematically beneficial to the group, as both attractors could possibly drive the group away from the truth (Fig. 5-Example 2). What happens in the case of conflicting interests, when the expert and the majority effects apply simultaneously and disagree with each other (Fig. 5-Example 3)? To investigate this issue, we conducted another series of simulations in which a cluster of low-confidence individuals sharing the same opinion Omaj, is facing a minority of high-confidence experts holding another opinion Oexp. As shown by Fig. 6A, the majority effect overcomes the expert effect when the proportion of experts pExp is lower than a certain threshold value located around 10%. However, as pExp increases from 10%, to 20% a transition occurs and the convergence point shifts from the majority to the experts’ opinion. Remarkably, this transition point remains stable even when a proportion pNeut of neutral individuals (defined as people with random opinions and a low confidence level) are present in the system (Fig. 6B). As pNeut increases above 70%, however, noise gradually starts to dominate, leading the expert and the majority effects to vanish. The tipping point occurring at a proportion of around 15% of experts appears to be a robust prediction, not only because it resists to a large amount of system noise (Fig. 6B), but also because a previous theoretical study using a completely different approach also reached a similar conclusion [40].


Social influence and the collective dynamics of opinion formation.

Moussaïd M, Kämmer JE, Analytis PP, Neth H - PLoS ONE (2013)

Which attractor dominates when the majority effect and the expert effect apply simultaneously?(A) The evolution of collective opinion when varying the relative proportion of experts pExp, holding an opinion Oexp and a high confidence level Cexp = 6, and the proportion of people in the majority group pmaj holding an opinion Omaj and a low confidence level randomly chosen in the interval Cmaj = [1 3]. Here, the number of neutral individuals is fixed to pNeut = 0. (B) Phase diagram showing the parameter space where the majority or the expert effects applies, when increasing the proportion of neutral individuals pNeut holding a random opinion and a low confidence level randomly chosen in the interval Cuni = [1 3]. The schematic regions delimited by black or white dashed lines show the zones where the collective opinion converges toward the majority or the expert opinion, respectively. In the transition zone, the collective opinion converges somewhere between Oexp and Omaj. In some rare cases, the crowd splits into two groups or more.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3818331&req=5

pone-0078433-g006: Which attractor dominates when the majority effect and the expert effect apply simultaneously?(A) The evolution of collective opinion when varying the relative proportion of experts pExp, holding an opinion Oexp and a high confidence level Cexp = 6, and the proportion of people in the majority group pmaj holding an opinion Omaj and a low confidence level randomly chosen in the interval Cmaj = [1 3]. Here, the number of neutral individuals is fixed to pNeut = 0. (B) Phase diagram showing the parameter space where the majority or the expert effects applies, when increasing the proportion of neutral individuals pNeut holding a random opinion and a low confidence level randomly chosen in the interval Cuni = [1 3]. The schematic regions delimited by black or white dashed lines show the zones where the collective opinion converges toward the majority or the expert opinion, respectively. In the transition zone, the collective opinion converges somewhere between Oexp and Omaj. In some rare cases, the crowd splits into two groups or more.
Mentions: Our simulations show that the majority effect and the expert effect are not systematically beneficial to the group, as both attractors could possibly drive the group away from the truth (Fig. 5-Example 2). What happens in the case of conflicting interests, when the expert and the majority effects apply simultaneously and disagree with each other (Fig. 5-Example 3)? To investigate this issue, we conducted another series of simulations in which a cluster of low-confidence individuals sharing the same opinion Omaj, is facing a minority of high-confidence experts holding another opinion Oexp. As shown by Fig. 6A, the majority effect overcomes the expert effect when the proportion of experts pExp is lower than a certain threshold value located around 10%. However, as pExp increases from 10%, to 20% a transition occurs and the convergence point shifts from the majority to the experts’ opinion. Remarkably, this transition point remains stable even when a proportion pNeut of neutral individuals (defined as people with random opinions and a low confidence level) are present in the system (Fig. 6B). As pNeut increases above 70%, however, noise gradually starts to dominate, leading the expert and the majority effects to vanish. The tipping point occurring at a proportion of around 15% of experts appears to be a robust prediction, not only because it resists to a large amount of system noise (Fig. 6B), but also because a previous theoretical study using a completely different approach also reached a similar conclusion [40].

Bottom Line: A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions.In particular, we identify two major attractors of opinion: (i) the expert effect, induced by the presence of a highly confident individual in the group, and (ii) the majority effect, caused by the presence of a critical mass of laypeople sharing similar opinions.These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.

View Article: PubMed Central - PubMed

Affiliation: Center for Adaptive Behavior and Cognition, Max Planck Institute for Human Development, Berlin, Germany.

ABSTRACT
Social influence is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. In our strongly interconnected society, social influence plays a prominent role in many self-organized phenomena such as herding in cultural markets, the spread of ideas and innovations, and the amplification of fears during epidemics. Yet, the mechanisms of opinion formation remain poorly understood, and existing physics-based models lack systematic empirical validation. Here, we report two controlled experiments showing how participants answering factual questions revise their initial judgments after being exposed to the opinion and confidence level of others. Based on the observation of 59 experimental subjects exposed to peer-opinion for 15 different items, we draw an influence map that describes the strength of peer influence during interactions. A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions. In particular, we identify two major attractors of opinion: (i) the expert effect, induced by the presence of a highly confident individual in the group, and (ii) the majority effect, caused by the presence of a critical mass of laypeople sharing similar opinions. Additional simulations reveal the existence of a tipping point at which one attractor will dominate over the other, driving collective opinion in a given direction. These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.

Show MeSH