AUTNES

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

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 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
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 nationa...
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
AUTNES Online Panel Study 2017-2019 (SUF Edition) Aug 27, 2020 Aichholzer, Julian; Partheymüller, Julia; Wagner, Markus; Kritzinger, Sylvia; Plescia, Carolina; Eberl, Jakob-Moritz; Meyer, Thomas; Berk, Nicolai; Büttner, Nico; Boomgaarden, Hajo; Müller, Wolfgang C., 2020, "AUTNES Online Panel Study 2017-2019 (SUF Edition)", https://doi.org/10.11587/QDETRI, AUSSDA, V1, UNF:6:PRC+g7z2YaNDAY0fxuvOkw== [fileUNF] Full edition for scientific use. The AUTNES Online Panel Study 2017–2019 is a thirteen-wave panel that focuses on the Austrian National Parliamentary Election held on 15 October 2017 and 29 September 2019. This survey is part of the Austrian National Election Study (AUTNES).
10096_da_de_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:LRa9bPT9mZKlPzrboPS73Q== DataSTATA Core data file - STATA format - 3615 Variables, 6624 Observations - German

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

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 nationa...

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

AUTNES Online Panel Study 2017-2019 (SUF Edition)

Aug 27, 2020

Aichholzer, Julian; Partheymüller, Julia; Wagner, Markus; Kritzinger, Sylvia; Plescia, Carolina; Eberl, Jakob-Moritz; Meyer, Thomas; Berk, Nicolai; Büttner, Nico; Boomgaarden, Hajo; Müller, Wolfgang C., 2020, "AUTNES Online Panel Study 2017-2019 (SUF Edition)", https://doi.org/10.11587/QDETRI, AUSSDA, V1, UNF:6:PRC+g7z2YaNDAY0fxuvOkw== [fileUNF]

Full edition for scientific use. The AUTNES Online Panel Study 2017–2019 is a thirteen-wave panel that focuses on the Austrian National Parliamentary Election held on 15 October 2017 and 29 September 2019. This survey is part of the Austrian National Election Study (AUTNES).

10096_da_de_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 - German

Add Data

Share Dataverse

Link Dataverse

Reset Modifications