Исследования иных дисциплин. Literature. Сообщества. Data. Familiar strangers. Every commuter knows them: strangers with familiar faces that accompany you day in day out. You know each other without really knowing each other. Perhaps, you might even nod at one another in the morning but don’t even know each other's name. Now, researchers paint a comprehensive picture of this secret network of familiar strangers. The number of commuters is constantly on the rise and the cities we live and move in are growing bigger and bigger.
Kay W. One big network Previous studies on social networks focused on contacts where the individuals already knew each other to a certain extent. “I found it astonishing how much the number of familiar strangers varies from one person to the next,” explains Axhausen. Infections, fashions, rumours This data is also interesting from a medical perspective as trains and buses actually constitute places with an increased risk of infection. Universal principle? Further reading: Sun L., Axhausen K.W., Lee D. Edwin Chen's Blog. Researchers develop new method for understanding network connections. Network science, the study of complex interconnected systems, has grown over the past few years as it has become pivotal in understanding a wide variety of fields ranging from molecular and cell biology to social and information sciences and big data.
By studying the structure and connectivity patterns of a network, researchers are able to gain insight into how different variables within a network are related and the strength of individual relationships, as well as make predictions about emerging network properties. In engineered networks, the connections between elements are directly observable. For most social, biological and information networks, the connections are only inferred based on the behavior of elements in the system across time or conditions.
“The challenge is that some elements may appear correlated in their activity patterns solely because they are both connected to a third party,” says Manolis Kellis, an associate professor of computer science at MIT.
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Software Applied for Social Sciences (Informática para às Ciênci.
Конференции. Data science. Qualitatitive Analsysis (CAQDA) Event Analysis.