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Sven Geboers c6f8540671 feat(right-wing): derive right-wing keywords via differential TF-IDF ... Implements U1: derive_keywords.py uses party voting patterns to classify motions as right-wing vs left-wing, then computes differential TF-IDF on cleaned motion titles to surface policy terms distinctive to right-wing motions. Key design choices: - Vote threshold: 60% of parties in group must vote 'voor' - Text cleaning strips motion prefixes aggressively (handles multi-word surnames, plural 'leden', t.v.v. parentheticals) - Expanded Dutch stopword list filters procedural and generic noise - Results written to analysis/right_wing/right_wing_keywords.json Produces ~50 filtered terms including: asielzoekers, defensie, kernenergie, boeren, vreemdelingenbeleid, stikstof, asielstop, strafrecht.		1 month ago
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derive_keywords.py	feat(right-wing): derive right-wing keywords via differential TF-IDF	1 month ago
right_wing_keywords.json	feat(right-wing): derive right-wing keywords via differential TF-IDF	1 month ago