By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-According to news reporting based on a preprint abstract, our journalists obtained the following quote sourced from os f.io: "The digital and computational revolutions have improved the prospects for analy zing the dynamics of large groups of interacting individuals. Digital trace data provide the type of large-scale, time-stamped, and granular information on soci al interactions that is needed to feasibly conduct research on social influence in non-experimental settings and to distinguish social influence effects from th e confounding effects of homophily. "This chapter reviews three concrete ways in which machine learning can improve the estimation of social influence effects from observational digital trace data .
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