Steps to run full analysis

Part 1: Prep

1. split_csv_to_txt.py to split the original .csv file into 5 .txt files (one for each rating level).
2. tokenize_english.py to run spaCy tokenization and lemmatization.
3. sample_random_lemmas.py to select random lemmas for the control group. Other specific lemmas for study should also be selected here.
4. (optional) stats.py to show info about how many tokens there are.

Part 2: Automated analysis

1. tf_idf.py to calculate all TF-IDF scores.
2. tf_idf_slope.py to calculate all slopes of TF-IDF scores relative to number of stars.
3. automated_final.py to calculate all final automated scores for eac
4. search_scores.py to grab scores for the targeted words.

Part 3: Manual analysis

1. print_context.py to find all instances of each lemma in context.
2. manual_scoring.py to manually assign scores to sampled context instances.

Part 4: Correlation between Automated and Manual scores

1. final_analysis.py to run a regression analysis on each of the groups.