The arXiv preprint (not yet peer-reviewed) introduces an automated pipeline combining 180-degree ambiguity correction, Bayesian Blocks segmentation, and statistical validation to detect electric vector position angle (EVPA) rotations in blazars. Applied to RoboPol monitoring data from 25 sources, it identified 48 rotations—including 27 previously unreported events, with 11 from the 2016-2017 season—spanning amplitudes of 90.8° to 359.7° and durations of 7 to 111.3 days. This re-analysis of the same dataset used in earlier manual catalogs shows systematic biases: rotations appear ~10% larger in amplitude, twice as long, and two-thirds slower than previously reported, highlighting how subjective segmentation can distort jet kinematics. The method also uncovers a correlation between longer-duration rotations and enhanced Fermi-LAT gamma-ray activity, suggesting these events trace particle acceleration episodes in relativistic jets, while amplitude alone shows no predictive power. This advances beyond the original RoboPol papers (e.g., Blinov et al. 2015 on initial monitoring results) and gamma-ray blazar studies (e.g., Hovatta et al. on multiwavelength correlations) by minimizing human bias and enabling scalable discovery. Limitations include reliance on existing RoboPol sampling cadence, potential over-segmentation in noisy data, and the absence of full multi-epoch VLBI imaging to confirm jet geometry links.