├── .gitignore ├── README.md ├── analysis ├── check_ocr_errors.py ├── choose_random_nouns.py ├── common.py ├── compute_foreign_born_props.py ├── count_country_mentions.py ├── count_nouns.py ├── count_speeches_and_tokens.py ├── count_tagged_lemmas.py ├── frame_terms.py ├── group_terms.py ├── identify_group_mentions.py ├── identify_immigrant_mentions.py ├── identify_metaphor_mentions.py ├── metaphor_terms.py └── run_metaphorical_analysis.py ├── annotations ├── export_comments.py ├── export_for_label_aggregation.py ├── measure_agreement.py └── tokenize.py ├── classification ├── make_predictions.py ├── make_predictions_tone.py ├── predict_on_all.py ├── predict_on_all_tone.py ├── run_final_model.py ├── run_final_model_tone.py ├── run_folds_hf.py ├── run_folds_hf_tone.py ├── run_linear_models.py ├── run_search_hf.py └── run_search_hf_tone.py ├── common └── functions.py ├── dw-nominate ├── combine_tone_and_demographics.ipynb ├── combine_tone_and_nominate.ipynb ├── datasheet_05-02-2022.csv ├── regression_demographic_tone.R └── speeches_with_tone_and_nominate.tsv ├── embeddings ├── convert_embeddings_to_word_probs.py ├── convert_embeddings_to_word_probs_all.py ├── embed_immigrant_terms_masked.py └── embed_metaphor_terms_masked.py ├── export ├── export_imm_segments_for_linear.py ├── export_imm_segments_with_metadata.py ├── export_imm_segments_with_tone_and_metadata.py ├── export_imm_speeches_for_scholar.py ├── export_imm_speeches_parsed.py └── export_tone_for_lr_models.py ├── hf ├── metrics.py ├── processors.py ├── run.py └── utils.py ├── linear ├── README.txt ├── create_partition.py ├── docs.py ├── evaluate_by_period.py ├── evaluation.py ├── export_weights.py ├── export_weights_npz.py ├── file_handling.py ├── get_shap_values.py ├── labels.py ├── predict.py ├── prediction_on_all.py ├── snowball.txt ├── train.py └── vocab.py ├── metadata ├── export_metadata.py ├── export_metadata_by_congress.py ├── export_metadata_by_congress_uscr.py ├── export_speech_dates.py ├── export_speech_lengths.py ├── export_speech_lengths_uscr.py ├── export_uscr_speech_dates.py └── load_metadata.py ├── parsing ├── common.py ├── parse_hein_bound.py ├── parse_uscr.py ├── preprocess_uscr.py ├── rejoin_into_pieces_by_congress.py ├── rejoin_into_pieces_by_congress_uscr.py ├── tokenize_hein.py └── tokenize_uscr.py ├── plotting ├── make_metaphor_plots.py ├── make_pmi_plots.py ├── make_pmi_plots_latin_america.py ├── make_stan_plots.py ├── make_tone_plots.py ├── make_tone_plots_binary.py ├── make_tone_plots_loo.py ├── make_tone_plots_probs_three.py ├── make_tone_plots_region.py └── plot_tone_of_annotations.py ├── presidential ├── collect_predictions.py ├── collect_predictions_binary.py ├── collect_predictions_linear.py ├── export_presidential_segments.py ├── select_keyword_segments.py ├── split_file.py └── tokenize_presidential.py ├── procedural ├── README.txt ├── collect_predictions.py ├── export_short_speeches.py ├── export_training_and_test.py └── model.nontest.tsv ├── public_opinion_and_sei ├── code │ ├── gallup_analysis.ipynb │ ├── gallup_data_analysis.do │ └── group_regressions.do ├── data │ └── input │ │ ├── datasheet_05-02-2022.csv │ │ ├── gallup_data.xlsx │ │ └── speech_data.csv ├── figures │ ├── SEI_graph.pdf │ └── anti_decreased_ys_yearfe_no_labels.pdf └── regressions │ └── share_anti_pro_regs.tex ├── relevance ├── collect_predictions.py ├── collect_predictions_linear.py ├── collect_predictions_val.py ├── combine_relevance_data.py ├── make_relevance_splits.py ├── make_relevance_splits_mid.py └── make_relevance_splits_modern.py ├── speech_selection ├── common.py ├── export_keyword_segments_early_with_overlap.py ├── export_keyword_segments_mid_with_overlap.py ├── export_keyword_segments_modern_with_overlap.py ├── export_keyword_segments_uscr.py ├── make_batches_early.py ├── make_batches_mid.py ├── make_batches_modern.py └── query_terms.py ├── stan └── run_final_model.py ├── time_periods └── common.py ├── tone ├── collect_predictions.py ├── 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