10.60507/FK2/BK14F8Schilling, JuliaJuliaSchilling0009-0005-4105-1415Universität BonnFuchs, RobertRobertFuchs0000-0001-7694-062XUniversität Bonnbonndata2025Arts and HumanitiesSchilling, JuliaJuliaSchillingUniversität Bonn2025-11-052025-11-11700771107038846946916161303972330359215442323106114200254918826326205331057511105883512827129131038899106text/csvtext/csvtext/csvtext/csvtext/csvtext/csvtext/csvtext/csvtext/csvtext/csvtext/markdowntext/x-r-notebooktext/x-python-scripttext/csvtext/csvtext/csvtext/csvtext/x-python-script1.0CC BY 4.0This repository contains all data and scripts used for the study “Project 2025 as a Technocratic Blueprint: A Corpus-Based Linguistic Analysis of Conservative Governance Discourse” (Schilling & Fuchs, 2025). The study investigates the language of the Heritage Foundation’s Project 2025, a 900-page conservative policy blueprint, using methods from Corpus-Assisted Discourse Studies (CADS), Political Discourse Analysis (PDA), and psycholinguistic text analysis. The corpus includes Project 2025 and Democratic and Republican Party platforms (2016–2024). The dataset includes: Raw data (/data/raw_data/): full texts of Project 2025 and party platforms in CSV format. Processed data (/data/raw_data/Project2025_lemmaPOS.csv): tokenized, lemmatized, and POS-tagged text. Keyness results (/data/keyness/): unigram and bigram keyness calculations (log-likelihood, log-ratio). Collocation results (/data/collocations/): top 10 adjective, noun, and verb collocates per node. LIWC results (/data/liwc/): LIWC-22 category scores for each corpus. Analysis scripts (/code/): R Markdown file (analysis_project2025.Rmd) and two Python scripts for collocation and keyness analysis. All files are in UTF-8 plain-text format. The dataset contains no personal, sensitive, or proprietary data and derives entirely from publicly accessible political documents.spaCy, 3.7R, 4.4.1RStudio, 2024.09.0+375Python, 3.11.8LIWC, 22