- see [[250520_171713 poland - strategies|poland strategies]] # strategy use "crowd" model: `mean(gpt4.1, deepseekv3-0324)` - [ ] maybe redo with gpt4o and deepseekv3 for robustness checks? (two models used in harris-trump study) ![[strategy_use.png]] for comparison, harris-trump exp below ![[20250513154051.png]] # lasso ```r # model formula persuasion~active_listening_and_empathy + aggressive_and_explicit_directives + audience_adaptation + build_rapport_and_common_ground + cognitive_elaboration + contrastive_tone2 + encourage_action_with_clear_calls + evidence_or_factbased_arguments + explicit_call_vote + localized_focus + negative_associations + negative_namecalling + negative_tone2 + politeness_and_civil_tone + positive_framing_and_value_alignment + positive_namecalling + positive_tone2 + preemptive_objections + reciprocity_and_mutual_benefit + relatable_hypotheticals + social_proof_and_normative_influence + stimulate_anger + stimulate_enthusiasm + storytelling_and_relatable_anecdotes + transfer_of_association + use_of_negative_testimonials + use_of_positive_testimonials + accuracyS + conditionZ * preZ * strategyZ # see todos/Qs below ``` todos/Qs - [ ] maybe also add two model dummies? gpt-vs-llama, gpt-vs-deepseek? - [ ] note that `strategyZ` (baseline vs nofacts) is also a predictor, in addition to `evidence_or_factbased_arguments` ![[1747167131.png]] for comparison, harris-trump exp below ![[20250513161244.png]] all coefficients below - `b`: lasso coef - `presence`: mean strategy use/presence ```r strategy b presence <char> <num> <num> 1: preZ 18.4284 NA 2: conditionZ 15.0313 NA 3: Evidence & facts 2.0685 0.4105 4: Contrast positives & negatives 1.5153 0.2057 5: Optimism & value alignment 1.0068 0.9199 6: Highlight own side positives 0.9975 0.7461 7: Build rapport 0.7917 0.5864 8: preZ:strategyZ 0.7776 NA 9: Positive testimonials 0.5576 0.0060 10: Positive name-calling 0.3904 0.6564 11: Stimulate enthusiasm 0.2860 0.6714 12: Facilitate action 0.2507 0.3266 13: Stimulate anger 0.2315 0.0636 14: Reciprocity 0.1778 0.1498 15: accuracyS 0.1757 NA 16: Negative testimonials 0.1701 0.0078 17: Negative name-calling 0.0946 0.0652 18: Personalization 0.0018 0.7025 19: Highlight opposition negatives 0.0000 0.0060 20: Localized focus 0.0000 0.1619 21: Politeness & civility 0.0000 0.9877 22: Positive associations 0.0000 0.7534 23: Relatable hypotheticals 0.0000 0.4881 24: conditionZ:preZ:strategyZ 0.0000 NA 25: strategyZ 0.0000 NA 26: Storytelling -0.0397 0.6134 27: Social influence -0.1098 0.0918 28: Cognitive elaboration -0.3005 0.4047 29: Being pushy -0.3072 0.0281 30: Explicit call to vote -0.3394 0.1284 31: conditionZ:strategyZ -0.3990 NA 32: Negative associations -0.4348 0.1915 33: Emphatic listening -1.0129 0.7958 34: Preemptive counter-arguments -1.0342 0.4837 35: conditionZ:preZ -15.6704 NA strategy b presence ```