Articles tagged with Network Structure
Researchers have developed an algorithm to discover communities and substructures in various networks, including genetic networks and social networks. The tool has been applied to identify community structures in co-expressed genes and social networks, and can also be used for sociological research.
Researchers found that companies connected through a small world network exhibit increased innovation and creativity, thanks to clustering and reach. This structure enables information exchange and cooperation among firms, leading to improved innovation outcomes.
The University of Pennsylvania researchers found that some of the simplest social networks function poorly and that information beyond a local view can hinder complicated networks' ability to accomplish tasks. In contrast, engineered or hierarchical structures proved easier for subjects to solve problems.
Researchers have developed a new method to find communities in large, complex networks, revealing structure and commonalities among members. The technique was tested on college football conferences with over 90% accuracy, showing promise for understanding systems like food webs and social networks.
Computer scientists at Cornell University have developed an algorithm to identify influential people in online communities. The method uses web crawlers to map communications links and can be applied to various goals such as product sales, disease prediction, or identifying terrorist leaders.