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License: AUSSDA Scientific Use Licence for data and CC BY for documentation

1,461 to 1,470 of 3,524 Results

AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition) Apr 9, 2021 - AUTNES Müller, Wolfgang C.; Bodlos, Anita; Dolezal, Martin; Eder, Nikolaus; Ennser-Jedenastik, Laurenz; Gahn, Christina; Graf, Elisabeth; Haselmayer, Martin; Haudum, Teresa; Huber, Lena Maria; Kaltenegger, Matthias; Meyer, Thomas M.; Praprotnik, Katrin; Reidinger, Verena; Winkler, Anna Katharina, 2021, "AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)", https://doi.org/10.11587/25P2WR, AUSSDA, V1, UNF:6:i67aYEm1NvbUjmVt3owwZA== [fileUNF] Full edition for scientific use. The AUTNES coding of party press releases covers all press releases that were issued by parties gaining at least two percent of the votes in the national elections 2002, 2006, 2008, 2013 and 2017. The coding procedure applies the AUTNES relational approach of recording subjects, predicates, and objects to press rele...
10726_co_en_v1_0.pdf Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition) Adobe PDF - 325.6 KB - MD5: e4bc02753fec8b213c4047a25bf7d1a3 CodebookDocumentation Codebook
10726_da_en_v1_0.tab Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition) Tabular Data - 10.1 MB - 43 Variables, 9943 Observations - UNF:6:mr84BrW8+myOXMArMBmVag== DataSTATA Core data file - compressed SPSS format - 43 Variables, 9943 Observations
10726_da_en_v1_0.zip Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition) ZIP Archive - 3.0 MB - MD5: 65c7dbadf693722009c4c2b43a165af8 CSVData Core data file - compressed csv format - 43 Variables, 9943 Observations
10726_da_en_v1_0.zsav Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition) Unknown - 6.4 MB - MD5: dd34b1e1cfcc297399a7b1e3d69236dd DataSPSS Core data file - compressed SPSS format - 43 Variables, 9943 Observations
10726_vi_en_v1_0.tab Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition) Tabular Data - 1.2 MB - 3 Variables, 32831 Observations - UNF:6:GpGTXFUnCq3M8S2BqT0G2Q== Documentation Variable identifiers and descriptions - machine-readable
COVID-19 Prevalence November 2020 (SUF edition) Feb 25, 2021 - COVID-19 Pandemic Paškvan, Matea; Kowarik, Alexander; Schrittwieser, Karin; Till, Matthias; Weinauer, Marlene; Göllner, Tobias; Hartleib, Sarah; Klimont, Jeanette; Plate, Marc; Baumgartner, Irene; Edelhofer-Lielacher, Edith; Grasser, Alfred; Kytir, Josef, 2021, "COVID-19 Prevalence November 2020 (SUF edition)", https://doi.org/10.11587/G3C2CS, AUSSDA, V1, UNF:6:mR15ezs0vMyYFjYgB0mgew== [fileUNF] Full edition for scientific use. The main purpose of the study was to identify the number of people actually infected with coronavirus in Austria, as well as the number of people who have formed antibodies against SARS-CoV-2 and thus have been infected and further to report how people are feeling during this crisis. A representative random sample o...
10736_co_de_v1_0.pdf Feb 25, 2021 - COVID-19 Prevalence November 2020 (SUF edition) Adobe PDF - 99.6 KB - MD5: 88e909556b5060fca76e4cd99685cb9a CodebookDocumentation Codebook
10736_da01_de_v1_0.tab Feb 25, 2021 - COVID-19 Prevalence November 2020 (SUF edition) Tabular Data - 2.7 MB - 221 Variables, 2711 Observations - UNF:6:DOnqfPZ5SlX5tSZAwC0yew== DataSTATA Core data file - STATA format - 221 Variables, 2711 Observations
10736_da01_de_v1_0.zip Feb 25, 2021 - COVID-19 Prevalence November 2020 (SUF edition) ZIP Archive - 220.0 KB - MD5: 31200ad884a6dadc806ad471996481dc Data Core data file - compressed CSV format - 221 Variables, 2711 Observations

AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)

Apr 9, 2021 - AUTNES

Müller, Wolfgang C.; Bodlos, Anita; Dolezal, Martin; Eder, Nikolaus; Ennser-Jedenastik, Laurenz; Gahn, Christina; Graf, Elisabeth; Haselmayer, Martin; Haudum, Teresa; Huber, Lena Maria; Kaltenegger, Matthias; Meyer, Thomas M.; Praprotnik, Katrin; Reidinger, Verena; Winkler, Anna Katharina, 2021, "AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)", https://doi.org/10.11587/25P2WR, AUSSDA, V1, UNF:6:i67aYEm1NvbUjmVt3owwZA== [fileUNF]

Full edition for scientific use. The AUTNES coding of party press releases covers all press releases that were issued by parties gaining at least two percent of the votes in the national elections 2002, 2006, 2008, 2013 and 2017. The coding procedure applies the AUTNES relational approach of recording subjects, predicates, and objects to press rele...

10726_co_en_v1_0.pdf

Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)

Adobe PDF - 325.6 KB -

CodebookDocumentation

Codebook

10726_da_en_v1_0.tab

Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)

Tabular Data - 10.1 MB - 43 Variables, 9943 Observations -

DataSTATA

Core data file - compressed SPSS format - 43 Variables, 9943 Observations

10726_da_en_v1_0.zip

Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)

ZIP Archive - 3.0 MB -

CSVData

Core data file - compressed csv format - 43 Variables, 9943 Observations

10726_da_en_v1_0.zsav

Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)

Unknown - 6.4 MB -

DataSPSS

Core data file - compressed SPSS format - 43 Variables, 9943 Observations

10726_vi_en_v1_0.tab

Apr 9, 2021 - AUTNES Content Analysis of Party Press Releases: Cumulative File (SUF edition)

Tabular Data - 1.2 MB - 3 Variables, 32831 Observations -

Documentation

Variable identifiers and descriptions - machine-readable

COVID-19 Prevalence November 2020 (SUF edition)

Feb 25, 2021 - COVID-19 Pandemic

Paškvan, Matea; Kowarik, Alexander; Schrittwieser, Karin; Till, Matthias; Weinauer, Marlene; Göllner, Tobias; Hartleib, Sarah; Klimont, Jeanette; Plate, Marc; Baumgartner, Irene; Edelhofer-Lielacher, Edith; Grasser, Alfred; Kytir, Josef, 2021, "COVID-19 Prevalence November 2020 (SUF edition)", https://doi.org/10.11587/G3C2CS, AUSSDA, V1, UNF:6:mR15ezs0vMyYFjYgB0mgew== [fileUNF]

Full edition for scientific use. The main purpose of the study was to identify the number of people actually infected with coronavirus in Austria, as well as the number of people who have formed antibodies against SARS-CoV-2 and thus have been infected and further to report how people are feeling during this crisis. A representative random sample o...

10736_co_de_v1_0.pdf

Feb 25, 2021 - COVID-19 Prevalence November 2020 (SUF edition)

Adobe PDF - 99.6 KB -

CodebookDocumentation

Codebook

10736_da01_de_v1_0.tab

Feb 25, 2021 - COVID-19 Prevalence November 2020 (SUF edition)

Tabular Data - 2.7 MB - 221 Variables, 2711 Observations -

DataSTATA

Core data file - STATA format - 221 Variables, 2711 Observations

10736_da01_de_v1_0.zip

Feb 25, 2021 - COVID-19 Prevalence November 2020 (SUF edition)

ZIP Archive - 220.0 KB -

Data

Core data file - compressed CSV format - 221 Variables, 2711 Observations

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