Data/code dictionary for project: - /Countries - crosscultural.R - primary analysis script for the country-level analyses. 3d Mind Model testing, individual dimension analyses, and model comparison with Circumplex, as well as permutation/bootstraping for inference on each. Visualization code for figures 1 and S1 (note: these also require files from naturalearthdata.com for the choropleth). This version of the analyses is more heavily commented than the historical and language versions - refer here for clarification if portion of those appear opaque. - Twitter/ - contains code for retrieving, geolocating, cleaning data from Twitter.com. Primary webscraping was carried out using [this][1] package. Auxiliary files are included to support geolocation, including shape files and cross-reference tables of geographical units. FastText code is also included ([this][2] docker container was used to process these data). - Vectors/ - Contains the raw word vectors extracted from each country's fastText embedding - /Dimensions - Contains two csv files with averaged human ratings of where each of 166 mental states falls on the dimensions of either the 3d Mind Model, or the Circumplex Model. The data were collected as part of another investigation (Tamir, Thornton, Contreras & Mitchell, 2016). The OSF repository for that project is linked. - Also contains 'filt.csv' which contains ratings of the pairwise similarity between the 166 mental states (used in the noise ceiling analysis at each level of analysis). - /Historical - combined_historic.R - primary analysis script for historical data - Vectors/ - Contains the raw word vectors extracted from each society's fastText embedding - Chinese/ - code and translations for analyzing the Classical Chinese corpus from the Chinese Text Project (https://ctext.org/). - Gutenberg/ - code and translations for analyzing the French and English portions of the Standardize Project Gutenberg Corpus (https://zenodo.org/record/2422561) - /Languages - crosslinguistic.R - primary analysis script for language level data. - proc_translated.sh - code for extracting translated terms from pretrained language vectors (downloaded from https://fasttext.cc/docs/en/crawl-vectors.html). - split_translations_to_txt.py - divides translated.csv into txt files for fastText - translated.csv - translated mental state terms - Vectors/ - Contains the raw word vectors extracted from each language's fastText embedding [1]: https://github.com/DominicBurkart/SocialNetworkAnalysis [2]: https://github.com/xeb/fastText-docker