Neural mechanisms tracking popularity in real-world social networks

Neural mechanisms tracking popularity in real-world social networks.

Differences in popularity are a key aspect of status in virtually all human groups and shape social interactions within them. Little is known, however, about how we track and neurally represent others' popularity. We addressed this question in two real-world social networks using sociometric methods to quantify popularity. Each group member (perceiver) viewed faces of every other group member (...

Characteristics of Social Networks in the Theory and the Real World

The development of information and communication technology as one of the most prominent components of the expansion of social networks has revolutionized the quantity, quality, and speed of information flow unprecedentedly. One of the important consequences of the discourse of globalization of communication is the expansion of virtual participatory politics, the politicization of ethnic, racia...

Discovering Motifs in Real-World Social Networks

We built a framework for analyzing the contents of large social networks, based on the approximate counting technique developed by Gonen and Shavitt. Our toolbox was used on data from a large forum— boards.ie—the most prominent community website in Ireland. For the purpose of this experiment, we were granted access to 10 years of forum data. This is the first time the approximate counting techn...

Using Neural Networks for Real - World

Predicting Content Popularity in Social Networks

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