- trump harris persuasion study - 8k AI messages - 27 strategies (16 generated by LLM + 11 from [Luke's paper](https://www.cambridge.org/core/journals/american-political-science-review/article/how-experiments-help-campaigns-persuade-voters-evidence-from-a-large-archive-of-campaigns-own-experiments/FF5BE6ED1553475F8321F7C4209357F7)) - see [[250131_112806 consolidated strategies v2|this doc for strategies]] - asked model to rate usage of each strategy - ratings: 0, 0.5, 1 # overall strategy use frequency across 8k AI messages ![[1738631541.png]] # strategy use for each condition ## mean ratings ![[1738630974.png]] # PCA ![[20250203181938.png]] most features load onto PC1; otherwise, it's messy (see below - after the heatmap for more) - pc2: negativity? - pc3: elaboration, deliberation, deep listening? - pc4: storytelling, anecdotes? ![[1738630510.png]] top 5 and bottom 5 features for each component ```r [1] "PC1" everything component feature component value feature_type <fctr> <fctr> <num> <char> 1: positive_framing_and_value_alignment PC1 0.7788080 top5 2: emotional_appeal_with_balanced_urgency PC1 0.7737796 top5 3: gradual_persuasion PC1 0.7659196 top5 4: politeness_and_civil_tone PC1 0.7179453 top5 5: transfer_of_association PC1 0.6760987 top5 6: social_proof_and_normative_influence PC1 0.2447723 bottom5 7: stimulate_anger PC1 0.2015709 bottom5 8: name-calling PC1 0.1830510 bottom5 9: use_of_positive_testimonials PC1 0.1198454 bottom5 10: use_of_negative_testimonials PC1 0.0872558 bottom5 [1] "PC2" negativity, trump component feature component value feature_type <fctr> <fctr> <num> <char> 1: negative_tone PC2 0.7266798 top5 2: name-calling PC2 0.5960550 top5 3: stimulate_anger PC2 0.5615600 top5 4: contrastive_tone PC2 0.5408932 top5 5: use_of_negative_testimonials PC2 0.4397736 top5 6: localized_focus PC2 -0.2385239 bottom5 7: positive_tone PC2 -0.3409390 bottom5 8: reciprocity_and_mutual_benefit PC2 -0.3453441 bottom5 9: stimulate_enthusiasm PC2 -0.3652947 bottom5 10: build_rapport_and_common_ground PC2 -0.3983873 bottom5 [1] "PC3" understanding, listening, empathy feature component value feature_type <fctr> <fctr> <num> <char> 1: cognitive_elaboration PC3 0.6032904 top5 2: active_listening_and_empathy PC3 0.5542455 top5 3: address_objections_and_counterarguments PC3 0.4205270 top5 4: reciprocity_and_mutual_benefit PC3 0.3660916 top5 5: gradual_persuasion PC3 0.2997194 top5 6: positive_tone PC3 -0.3271521 bottom5 7: transfer_of_association PC3 -0.4669102 bottom5 8: encourage_action_with_clear_calls PC3 -0.5314675 bottom5 9: stimulate_enthusiasm PC3 -0.5606148 bottom5 10: aggressive_and_explicit_directives PC3 -0.6410724 bottom5 [1] "PC4" story telling, anecdotes feature component value feature_type <fctr> <fctr> <num> <char> 1: use_of_everyday_people_as_messengers PC4 0.6153169 top5 2: localized_focus PC4 0.4594400 top5 3: use_of_positive_testimonials PC4 0.3799987 top5 4: social_proof_and_normative_influence PC4 0.3463055 top5 5: storytelling_and_relatable_anecdotes PC4 0.2788590 top5 6: cognitive_elaboration PC4 -0.1246677 bottom5 7: gradual_persuasion PC4 -0.2553949 bottom5 8: positive_framing_and_value_alignment PC4 -0.2591820 bottom5 9: positive_tone PC4 -0.2733063 bottom5 10: politeness_and_civil_tone PC4 -0.3451707 bottom5 [1] "PC5" building rapport with negativity feature component value feature_type <fctr> <fctr> <num> <char> 1: name-calling PC5 0.4403572 top5 2: build_rapport_and_common_ground PC5 0.4116369 top5 3: use_of_negative_testimonials PC5 0.4103404 top5 4: active_listening_and_empathy PC5 0.3469322 top5 5: negative_tone PC5 0.1860533 top5 6: aggressive_and_explicit_directives PC5 -0.1601957 bottom5 7: address_objections_and_counterarguments PC5 -0.2343283 bottom5 8: localized_focus PC5 -0.2908333 bottom5 9: relatable_hypotheticals PC5 -0.3414939 bottom5 10: evidence-_or_fact-based_arguments PC5 -0.4358370 bottom5 [1] "PC6" feature component value feature_type <fctr> <fctr> <num> <char> 1: use_of_positive_testimonials PC6 0.6931575 top5 2: use_of_everyday_people_as_messengers PC6 0.2579346 top5 3: contrastive_tone PC6 0.1850435 top5 4: evidence-_or_fact-based_arguments PC6 0.1733547 top5 5: positive_tone PC6 0.1579372 top5 6: encourage_action_with_clear_calls PC6 -0.1933386 bottom5 7: audience_adaptation PC6 -0.2024014 bottom5 8: reciprocity_and_mutual_benefit PC6 -0.2227717 bottom5 9: localized_focus PC6 -0.2771537 bottom5 10: stimulate_anger PC6 -0.3192187 bottom5 [1] "PC7" feature component value feature_type <fctr> <fctr> <num> <char> 1: social_proof_and_normative_influence PC7 0.6523818 top5 2: evidence-_or_fact-based_arguments PC7 0.2052370 top5 3: stimulate_anger PC7 0.1860397 top5 4: encourage_action_with_clear_calls PC7 0.1536522 top5 5: aggressive_and_explicit_directives PC7 0.1203791 top5 6: transfer_of_association PC7 -0.1185417 bottom5 7: use_of_everyday_people_as_messengers PC7 -0.1314816 bottom5 8: name-calling PC7 -0.1319323 bottom5 9: relatable_hypotheticals PC7 -0.2105588 bottom5 10: storytelling_and_relatable_anecdotes PC7 -0.4576658 bottom5 [1] "PC8" feature component value feature_type <fctr> <fctr> <num> <char> 1: use_of_negative_testimonials PC8 0.5949265 top5 2: localized_focus PC8 0.3207318 top5 3: evidence-_or_fact-based_arguments PC8 0.2294022 top5 4: positive_tone PC8 0.1725357 top5 5: stimulate_enthusiasm PC8 0.1176925 top5 6: build_rapport_and_common_ground PC8 -0.1371894 bottom5 7: audience_adaptation PC8 -0.1687177 bottom5 8: aggressive_and_explicit_directives PC8 -0.1960477 bottom5 9: active_listening_and_empathy PC8 -0.2113021 bottom5 10: stimulate_anger PC8 -0.2825027 bottom5 [1] "PC9" feature component value feature_type <fctr> <fctr> <num> <char> 1: use_of_everyday_people_as_messengers PC9 0.32866571 top5 2: audience_adaptation PC9 0.31429251 top5 3: localized_focus PC9 0.17049784 top5 4: use_of_positive_testimonials PC9 0.12704508 top5 5: evidence-_or_fact-based_arguments PC9 0.11078176 top5 6: emotional_appeal_with_balanced_urgency PC9 -0.06383895 bottom5 7: name-calling PC9 -0.13359499 bottom5 8: relatable_hypotheticals PC9 -0.22299481 bottom5 9: social_proof_and_normative_influence PC9 -0.43092697 bottom5 10: storytelling_and_relatable_anecdotes PC9 -0.43336313 bottom5 [1] "PC10" feature component value feature_type <fctr> <fctr> <num> <char> 1: use_of_negative_testimonials PC10 0.3913890 top5 2: use_of_positive_testimonials PC10 0.3541201 top5 3: aggressive_and_explicit_directives PC10 0.2760644 top5 4: encourage_action_with_clear_calls PC10 0.1805196 top5 5: storytelling_and_relatable_anecdotes PC10 0.1671059 top5 6: localized_focus PC10 -0.1874561 bottom5 7: negative_tone PC10 -0.1879528 bottom5 8: name-calling PC10 -0.2087545 bottom5 9: social_proof_and_normative_influence PC10 -0.2115479 bottom5 10: use_of_everyday_people_as_messengers PC10 -0.2260449 bottom5 [1] "PC11" feature component value feature_type <fctr> <fctr> <num> <char> 1: use_of_everyday_people_as_messengers PC11 0.4156124 top5 2: aggressive_and_explicit_directives PC11 0.1905905 top5 3: use_of_negative_testimonials PC11 0.1851716 top5 4: social_proof_and_normative_influence PC11 0.1657042 top5 5: contrastive_tone PC11 0.0985911 top5 6: name-calling PC11 -0.1059363 bottom5 7: emotional_appeal_with_balanced_urgency PC11 -0.1221705 bottom5 8: stimulate_anger PC11 -0.2662746 bottom5 9: localized_focus PC11 -0.2869204 bottom5 10: use_of_positive_testimonials PC11 -0.3751052 bottom5 [1] "PC12" feature component value feature_type <fctr> <fctr> <num> <char> 1: stimulate_anger PC12 0.3695700 top5 2: use_of_everyday_people_as_messengers PC12 0.2742338 top5 3: politeness_and_civil_tone PC12 0.1704799 top5 4: emotional_appeal_with_balanced_urgency PC12 0.1449118 top5 5: positive_framing_and_value_alignment PC12 0.1351281 top5 6: name-calling PC12 -0.1518101 bottom5 7: reciprocity_and_mutual_benefit PC12 -0.1594460 bottom5 8: build_rapport_and_common_ground PC12 -0.1638914 bottom5 9: contrastive_tone PC12 -0.1798421 bottom5 10: audience_adaptation PC12 -0.3571513 bottom5 [1] "PC13" feature component value feature_type <fctr> <fctr> <num> <char> 1: reciprocity_and_mutual_benefit PC13 0.4408247 top5 2: aggressive_and_explicit_directives PC13 0.2106336 top5 3: name-calling PC13 0.2070898 top5 4: encourage_action_with_clear_calls PC13 0.1995851 top5 5: use_of_everyday_people_as_messengers PC13 0.1143203 top5 6: social_proof_and_normative_influence PC13 -0.1253331 bottom5 7: transfer_of_association PC13 -0.1340864 bottom5 8: use_of_negative_testimonials PC13 -0.1444289 bottom5 9: stimulate_anger PC13 -0.1695354 bottom5 10: audience_adaptation PC13 -0.2907530 bottom5 [1] "PC14" feature component value feature_type <fctr> <fctr> <num> <char> 1: reciprocity_and_mutual_benefit PC14 0.33447281 top5 2: contrastive_tone PC14 0.25491711 top5 3: stimulate_anger PC14 0.20707721 top5 4: positive_tone PC14 0.15449566 top5 5: use_of_negative_testimonials PC14 0.09828821 top5 6: audience_adaptation PC14 -0.11482166 bottom5 7: politeness_and_civil_tone PC14 -0.12296126 bottom5 8: localized_focus PC14 -0.14321321 bottom5 9: gradual_persuasion PC14 -0.15375755 bottom5 10: name-calling PC14 -0.32077062 bottom5 ```