Study Looks at How Social Networks Affect Consensus

A month before the fall of the Berlin Wall, 70,000 people gathered in the streets of Leipzig, East Germany, on Oct. 9, 1989, to demonstrate against the communist regime and demand democratic reforms. Clearly, no central authority planned this event; so how did all of these people decide to come together on that particular day?

A new study by researchers at Northwestern University sheds light on how individuals might obtain information about the decisions and preferences of other individuals with whom they do not have a relationship or even contact. The findings were published by the Proceedings of the National Academy of Sciences (PNAS).

The Leipzig demonstration is an example of a complex system, the result of an evolving process. The common characteristic of complex systems, whether they be social or biological in nature, is that they display organization without any external organizing principle being applied.

“How did a consensus come about? Our computer model shows how social networks can substitute for central mechanisms in decision making,” said Luís A. N. Amaral, associate professor of chemical and biological engineering and an author on the PNAS paper. “Surprisingly, information can be aggregated more efficiently if local information transmission is not perfectly reliable but is subject to error or random noise, due to lack of trust, indecision or unreliable information technologies.”

For the citizens of Leipzig, the “noise” was the presence of the Stasi, the state secret police. “The need of individuals to avoid certain forms of communication, due to fear of the Stasi, might actually have contributed to the more efficient spread of information about a generalized dissatisfaction with the regime and the willingness to take a stand against it,” said Amaral.

The Northwestern study also clarifies how social norms might quickly be adopted and remain ingrained within society and how unicellular organisms might organize into multi-cellular structures.

The researchers show that a simple majority rule approach, in which each unit -- a person or a cell -- adopts the state of the majority of its neighbors within an intricate communication network, can efficiently lead to global organization. The model is adaptable and robust -- a real-world system capable of responding to external conditions.

“In real life we use simple rules to decide what to do,” said Amaral. “People tend to adjust their opinions based on what the majority is telling them.”

In addition to Amaral, other authors on the PNAS paper are André A. Moreira, Abhishek Mathur and Daniel Diermeier, from Northwestern University. Diermeier is co-director of Northwestern’s Institute for Complex Systems.

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