CfP Entropy special Issue «Information Theory for Human and Social Processes»

Shannon famously applied his “mathematical theory of communication” to human communication, alledgedly having his wife, Betty, estimating word probabilities to calcualte the first approximation of the entropy of English. The following decades have seen creative further applications to humans and social processes (e.g., Miller, 1956; Attneave, 1959; Coleman, 1975; Ellis and Fisher, 1975; Cappella, 1979). These efforts lost steam in the 1980s, mainly because of the lack of adequate data, and limited computational power. Both limitations do not apply anymore. The increase in human interactions taking place in digital environments has led to an abundance of behavioral “big data”, enough even to calculate measures that converge rather slowly.
This Special Issue compiles creative research on the innovative uses of information theory, and its extensions, to better understand human behavior and social processes. Among other topics, the focus is set on human communication, social organization, human–machine interaction, collaborative teamwork, social media dynamics, and cognitive and machine baises—all online and/or offline.
Deadline Jan 2020. Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Full call for papers here.