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Revisiting the Objective of Echo Chamber Detection
In this paper, we study the detection of an echo chamber in a social network, i.e., the identification of a set of nodes that agree on a topic, while disagreeing with the rest of nodes. We argue that this problem is different from other social network analysis problems such as community detection, and from other graph problems such as maximum graph cut and maximum clique. To the best of our knowledge, we are the first to formalize the objective function of echo chamber detection, by using the theory of Fourier transforms of set functions (Stobbe and Krause, 2012). We propose scalable semidefin
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-16T12:09:57.000Z
First collected: 2026-09-20T08:01:03.945Z. This is not the publication date.