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Real Network Control Understanding how complex networks are controlled has implications for a variety of real-world networks, from traffic safety to transcriptional control. Ruths and Ruths (p. 1373 ; see the Perspective by Onnela ) have developed a theoretical framework for analyzing individual controls within networks based on numbers of sources and sinks for information flow. By this method, the number of controls required by a network can be predicted and direct comparisons for the basis for control across networks of differing size, structure, and function can be made. Although three broad classes of real networks were observed, current, established random models of networks were insufficient to model their control structures.

On 3 November 1948, the day after Harry Truman won the United States presidential elections, the Chicago Tribune published one of the most famous erroneous headlines in newspaper history: “Dewey Defeats Truman” ( 1 , 2 ). The headline was informed by telephone surveys, which had inadvertently undersampled Truman supporters ( 1 ). Rather than permanently discrediting the practice of polling, this event led to the development of more sophisticated techniques and higher standards that produce the more accurate and statistically rigorous polls conducted today ( 3 ).

Campbell, Shea, and Albert propose an adaptation of the Barabasi-Albert model of network formation that permits a level of tuning of the control profiles of these networks. We point out some limitations and generalizations of this method as well as highlight opportunities for future work to refine formation mechanisms to provide control profile tuning in synthetic networks.