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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281 to 290 of 374 Results

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 contains the following steps: (1) Sampling 12713 sentences from Austrian par...
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
Training Data for German Sentiment Analysis of Political Communication (SUF edition) Nov 26, 2020 Haselmayer, Martin; Jenny, Marcelo, 2020, "Training Data for German Sentiment Analysis of Political Communication (SUF edition)", https://doi.org/10.11587/EOPCOB, AUSSDA, V1, UNF:6:wx/QlNpI73mL4r3N+cNhBg== [fileUNF] Full edition for scientific use. The dataset contains 125871 sentences extracted from Austrian parliamentary debates and party press releases. Press releases were collected under the auspices of the Austrian National Election Study (AUTNES) and cover 6 weeks prior to each national election 1995-2013. Data from parliamentary debates stem from a rand...
10273_da_de_v1_0.tab Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition) Tabular Data - 22.3 MB - 7 Variables, 125871 Observations - UNF:6:IiVRvJlBGz0ZxTi2febxHA== DataSTATA Core data file - STATA format - 7 Variables, 125871 Observations
10273_da_de_v1_0.zsav Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition) Unknown - 8.7 MB - MD5: e3f5c926014383e982a9ec524e04e8cc DataSPSS Core data file - compressed SPSS format - 7 Variables, 125871 Observations
10273_mr_en_v1_0.pdf Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition) Adobe PDF - 84.7 KB - MD5: 956d09f91536890f37733442f4b5a62f DocumentationMethod report Method report
10273_vi_de_v1_0.tab Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition) Tabular Data - 448 B - 3 Variables, 13 Observations - UNF:6:Ze7yJiIAaxcdxsnaJ9Kesg== Documentation Variable identifiers and descriptions - machine-readable
10096_da_de_v1_0.zsav Aug 27, 2020 - AUTNES Online Panel Study 2017-2019 (SUF Edition) Unknown - 16.3 MB - MD5: 68217c20a8c8e6abce96474ff0313f5d DataSPSS Core data file - compressed SPSS format - 3615 Variables, 6624 Observations - German
10096_da_en_v1_0.tab Aug 27, 2020 - AUTNES Online Panel Study 2017-2019 (SUF Edition) Tabular Data - 33.9 MB - 3615 Variables, 6624 Observations - UNF:6:+byRaCn1cbzWgy3vtqfzOg== DataSTATA Core data file - STATA format - 3615 Variables, 6624 Observations - English

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 contains the following steps: (1) Sampling 12713 sentences from Austrian par...

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

Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Nov 26, 2020

Haselmayer, Martin; Jenny, Marcelo, 2020, "Training Data for German Sentiment Analysis of Political Communication (SUF edition)", https://doi.org/10.11587/EOPCOB, AUSSDA, V1, UNF:6:wx/QlNpI73mL4r3N+cNhBg== [fileUNF]

Full edition for scientific use. The dataset contains 125871 sentences extracted from Austrian parliamentary debates and party press releases. Press releases were collected under the auspices of the Austrian National Election Study (AUTNES) and cover 6 weeks prior to each national election 1995-2013. Data from parliamentary debates stem from a rand...

10273_da_de_v1_0.tab

Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Tabular Data - 22.3 MB - 7 Variables, 125871 Observations -

DataSTATA

Core data file - STATA format - 7 Variables, 125871 Observations

10273_da_de_v1_0.zsav

Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Unknown - 8.7 MB -

DataSPSS

Core data file - compressed SPSS format - 7 Variables, 125871 Observations

10273_mr_en_v1_0.pdf

Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Adobe PDF - 84.7 KB -

DocumentationMethod report

Method report

10273_vi_de_v1_0.tab

Nov 26, 2020 - Training Data for German Sentiment Analysis of Political Communication (SUF edition)

Tabular Data - 448 B - 3 Variables, 13 Observations -

Documentation

Variable identifiers and descriptions - machine-readable

10096_da_de_v1_0.zsav

Aug 27, 2020 - AUTNES Online Panel Study 2017-2019 (SUF Edition)

Unknown - 16.3 MB -

DataSPSS

Core data file - compressed SPSS format - 3615 Variables, 6624 Observations - German

10096_da_en_v1_0.tab

Aug 27, 2020 - AUTNES Online Panel Study 2017-2019 (SUF Edition)

Tabular Data - 33.9 MB - 3615 Variables, 6624 Observations -

DataSTATA

Core data file - STATA format - 3615 Variables, 6624 Observations - English

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