When talking about what become more influential superspreaders of information on social networks a study has revealed that ‘smaller is smarter’.

City College of New York (CCNY) physicists Flaviano Morone and Hernan A. Makse said it a major shift which could have some significant consequences for a broad range of social, natural and living networked systems.

Makse further affirmed that the problem of recognizing the minimal set of influential nodes in complex networks for maximizing viral marketing in social media, optimizing immunization campaigns and protecting networks under attack is one of the most studied problems in network science.

Morone and Makse tried to solve the problem by applying ‘rigorous theoretical solutions and systematic benchmarking’. They even proposed a scalable algorithm, called Collective Influence algorithm, which they believe is far better than all other competing methods in large social networks like Twitter and Facebook which have more than 100 million users.

Through rigorous mathematical calculations, employing optimal percolation and state-of-the-art spin glass theory, they were successful in solving the optimal collective influence problem in random networks, Morone said.

They showed that the set of optimal superspreaders radically differ and is much smaller than that obtained by all previous heuristics rankings, including PageRank, the basis of Google.

According to CCNY researchers, their theory showed that top influencers are highly counterintuitive: weakly connected people strategically surrounded by hierarchical coronas of hubs are the most powerful influencers.

Their work provides a theoretical revision to the current view on influence, marking an exemplar shift from ‘bigger is better’ to ‘smaller is smarter’. Researchers stated that these results will appeal to an extensive range of scientists in fields such as networks, physics, mathematics, epidemiology, marketing, as well as to officials monitoring the spread of contagious diseases like the Ebola outbreak, added Makse.