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    Evaluating Stability in Massive Social Networks: Efficient Streaming Algorithms for Structural Balance

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    Polarization and multiscale structural balance in signed networks

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    Polarization is a common feature of social systems. Structural Balance Theory studies polarization of positive in-group and negative out-group ties in terms of semicycles within signed networks. However, enumerating semicycles is computationally expensive, so approximations are often needed to assess balance. Here we introduce Multiscale Semiwalk Balance (MSB) approach for quantifying the degree of balance (DoB) in (un)directed, (un)weighted signed networks by approximating semicycles with closed semiwalks. MSB allows principled selection of a range of cycle lengths appropriate for assessing DoB and interpretable under the Locality Principle (which posits that patterns in shorter cycles are crucial for balance). This flexibility overcomes several limitations affecting walk-based approximations and enables efficient, interpretable methods for measuring DoB and clustering signed networks. We demonstrate the effectiveness of our approach by applying it to real-world social systems. For instance, our methods capture increasing polarization in the U.S. Congress, which may go undetected with other methods.Comment: 29 pages; 7 figures; preprint before peer revie
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