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R Syntax - 3.5 KB - MD5: 869756a1e078f338de13baf855c1f109
R script for exact cone angle
ZIP Archive - 34.0 MB - MD5: 219e6041a7b592c97980334421fc0b2d
Gaussian .log files
HTML - 17.3 KB - MD5: baa655b30e8d851bca8c806fe76dbd7d
2026. aasta migratsiooni käigus varasemast DataDOI süsteemist üle kantud kasutusstatistika kajastab tegevust eelmises DSpace-põhises süsteemis ega näita Dataverse’i uusi kasutusandmeid. Usage statistics carried over from the previous DataDOI system as part of the 2026 migration reflect activity in the former DSpace-based system and do not represent...
ZIP Archive - 46.6 KB - MD5: b0e7609d97734d5183433655a4d29dac
Optimized geometries in the gas phase and in solvent
MS Excel Spreadsheet - 58.4 KB - MD5: c8469782ed767408fc15f3dbd01b6324
Corrected excel file with calculated properties
MS Excel Spreadsheet - 50.6 KB - MD5: cf1cb5c9e2c28d1146abdfa5ad7b1502
Old version of excel file with calculated properties
Plain Text - 1.3 KB - MD5: 9207c370a6483fe79ef9a364b318fcc3
README
Mar 24, 2025 - Poliitikauuringute andmed
Mölder, Martin; Mollona, Edoardo; Diana, Alessio, 2025, "Topic Models from GAFAM Discourse", https://doi.org/10.23673/RE-506, DATADOI, V1
This dataset contains the results of an LDA topic model with 200 topics that was applied to a combined corpus of newspaper articles about GAFAM (Google, Amazon, Facebook, Apple, Microsoft) companies (113 123 texts). The objective of this analysis was to analyze what discourses arise in public in relation to GAFAM companies and how the company disco...
Comma Separated Values - 108.0 MB - MD5: 2cba99e9ce28a806238ee16ee2d87c6e
Metadata about all the documents that were used for the topic modeling analysis.
Comma Separated Values - 293.1 MB - MD5: 4819c30dc7b835b9091efa4777b2f78b
A file were each row corresponds to a document in the corpus that was used for the analysis, each column indicates a topic that the model determined and the cell values indicate the estimated proportion of the topic in that particular document.
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