AUTNES

AUTNES - Austrian National Election Study is engaged in the comprehensive social science analysis of Austrian national elections. AUTNES is part of the Vienna Center for Electoral Research (VieCER).

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261 to 270 of 374 Results

10723_da_en_v1_0.zsav Jan 27, 2021 - AUTNES Content Analysis of Party Manifestos 2017 (SUF edition) Unknown - 2.4 MB - MD5: a759223c905076a1e90699cfe38c656e DataSPSS Core data file - compressed SPSS format - 18 Variables, 25557 Observations
10723_vi_en_v1_0.tab Jan 27, 2021 - AUTNES Content Analysis of Party Manifestos 2017 (SUF edition) Tabular Data - 443.5 KB - 3 Variables, 11866 Observations - UNF:6:NElkxsXguNNsA66H/yb/XA== Documentation Variable identifiers and descriptions - machine-readable
10724_co_en_v1_0.pdf Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition) Adobe PDF - 307.6 KB - MD5: 13a8234eba6443709a0ef21f8213d071 CodebookDocumentation Codebook
10724_da_en_v1_0.tab Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition) Tabular Data - 29.7 MB - 33 Variables, 77573 Observations - UNF:6:Y6Z5/MsaStVMBoiSBddTAA== DataSTATA Core data file, STATA format - 33 Variables, 77573 Observations
10724_da_en_v1_0.zsav Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition) Unknown - 10.4 MB - MD5: 20dd6d0e8385775f2e14eb8806933400 DataSPSS Core data file - compressed SPSS format - 33 Variables, 77573 Observations
10724_mr_en_v1_0.pdf Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition) Adobe PDF - 774.1 KB - MD5: b813de2b5968c827a30c4f8d54779ae8 DocumentationMethod report Method report
10724_vi_en_v1_0.tab Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition) Tabular Data - 445.1 KB - 3 Variables, 11911 Observations - UNF:6:yjFhsObnuv4OUh7FcwKMng== Documentation Variable identifiers and descriptions - machine-readable
The German Political Sentiment Dictionary (SUF edition) Dec 2, 2020 Haselmayer, Martin; Jenny, Marcelo, 2020, "The German Political Sentiment Dictionary (SUF edition)", https://doi.org/10.11587/7PFLIU, AUSSDA, V1, UNF:6:fddvmzxSkM88VgrqvxOqTg== [fileUNF] Full edition for scientific use. This dataset contains a German-language sentiment dictionary of 5001 negative words and their associated sentiment strength on a five-point-scale from 0 (not negative) to 4 (very strongly negative). The procedure for building the dictionary contai...
10274_da_de_v1_0.tab Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition) Tabular Data - 399.2 KB - 8 Variables, 5001 Observations - UNF:6:fddvmzxSkM88VgrqvxOqTg== DataSTATA Core data file - STATA format - 8 Variables, 5001 Observations
10274_mr_en_v1_0.pdf Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition) Adobe PDF - 62.9 KB - MD5: 050d20c9d45e62745c30f748be8cb9ed DocumentationMethod report Method report

10723_da_en_v1_0.zsav

Jan 27, 2021 - AUTNES Content Analysis of Party Manifestos 2017 (SUF edition)

Unknown - 2.4 MB -

DataSPSS

Core data file - compressed SPSS format - 18 Variables, 25557 Observations

10723_vi_en_v1_0.tab

Jan 27, 2021 - AUTNES Content Analysis of Party Manifestos 2017 (SUF edition)

Tabular Data - 443.5 KB - 3 Variables, 11866 Observations -

Documentation

Variable identifiers and descriptions - machine-readable

10724_co_en_v1_0.pdf

Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition)

Adobe PDF - 307.6 KB -

CodebookDocumentation

Codebook

10724_da_en_v1_0.tab

Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition)

Tabular Data - 29.7 MB - 33 Variables, 77573 Observations -

DataSTATA

Core data file, STATA format - 33 Variables, 77573 Observations

10724_da_en_v1_0.zsav

Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition)

Unknown - 10.4 MB -

DataSPSS

Core data file - compressed SPSS format - 33 Variables, 77573 Observations

10724_mr_en_v1_0.pdf

Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition)

Adobe PDF - 774.1 KB -

DocumentationMethod report

Method report

10724_vi_en_v1_0.tab

Dec 17, 2020 - AUTNES Content Analysis of Party Manifestos: Cumulative File (SUF edition)

Tabular Data - 445.1 KB - 3 Variables, 11911 Observations -

Documentation

Variable identifiers and descriptions - machine-readable

The German Political Sentiment Dictionary (SUF edition)

Dec 2, 2020

Haselmayer, Martin; Jenny, Marcelo, 2020, "The German Political Sentiment Dictionary (SUF edition)", https://doi.org/10.11587/7PFLIU, AUSSDA, V1, UNF:6:fddvmzxSkM88VgrqvxOqTg== [fileUNF]

Full edition for scientific use. This dataset contains a German-language sentiment dictionary of 5001 negative words and their associated sentiment strength on a five-point-scale from 0 (not negative) to 4 (very strongly negative). The procedure for building the dictionary contai...

10274_da_de_v1_0.tab

Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition)

Tabular Data - 399.2 KB - 8 Variables, 5001 Observations -

DataSTATA

Core data file - STATA format - 8 Variables, 5001 Observations

10274_mr_en_v1_0.pdf

Dec 2, 2020 - The German Political Sentiment Dictionary (SUF edition)

Adobe PDF - 62.9 KB -

DocumentationMethod report

Method report

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