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

1,331 to 1,340 of 3,499 Results

10061_readme.pdf Oct 8, 2021 - AUTNES Content Analysis of Party Facebook Pages 2013 (SUF edition) Adobe PDF - 48.5 KB - MD5: 266773685764e5f21ab69eb920237088 Documentation Data curation protocol
10061_vi_en_v1_0.tab Oct 8, 2021 - AUTNES Content Analysis of Party Facebook Pages 2013 (SUF edition) Tabular Data - 1.9 MB - 3 Variables, 52157 Observations - UNF:6:Q0wakaAYSS3UX5LT+DEVGw== Documentation Variable identifiers and descriptions - machine-readable
AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition) Sep 14, 2021 - AUTNES Müller, Wolfgang C.; Bodlos, Anita; Ennser-Jedenastik, Laurenz; Graf, Elisabeth; Haselmayer, Martin; Haudum, Teresa; Huber, Lena Maria; Meyer, Thomas M.; Reidinger, Verena, 2021, "AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)", https://doi.org/10.11587/SFCAOO, AUSSDA, V1, UNF:6:7rxSZYniYODoo0eWQ8bfgw== [fileUNF] Full edition for scientific use. The AUTNES dataset on party newspaper ads 2017 contains data on advertisements published in Austria's leading newspapers (Der Standard, Die Presse, Heute, Kleine Zeitung, Kronen Zeitung, Kurier, Österreich, Salzburger Nachrichten) within the last six weeks before the 2017 national election. The coding procedure appl...
10727_co_en_v1_0.pdf Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition) Adobe PDF - 547.2 KB - MD5: 63eb262c8f1d904d2e5fe30b788e0a6c CodebookDocumentation Codebook
10727_da_en_v1_0.tab Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition) Tabular Data - 53.9 KB - 52 Variables, 274 Observations - UNF:6:MRpTLwv1Khr/CsGkyUeYlg== DataSTATA Core data file - STATA format - 52 Variables, 274 Observations
10727_da_en_v1_0.zip Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition) ZIP Archive - 5.8 KB - MD5: d25606a730d9260b39a1ac3f49340964 CSVData Core data file - compressed csv format - 52 Variables, 274 Observations
10727_da_en_v1_0.zsav Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition) Unknown - 1.8 MB - MD5: 53bd00982a2b41192612c738bf8aba75 DataSPSS Core data file - compressed SPSS format - 52 Variables, 274 Observations
10727_vi_en_v1_0.tab Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition) Tabular Data - 2.0 MB - 3 Variables, 57562 Observations - UNF:6:82Dcd5J/5WSFxi0pnxDRrw== Documentation Variable identifiers and descriptions - machine-readable
Polarization in public opinion: Combining social surveys and big data analyses of Twitter (SUF Edition) Sep 13, 2021 - COVID-19 Pandemic Hadler, Markus; Klösch, Beate; Lex, Elisabeth; Reiter-Haas, Markus, 2021, "Polarization in public opinion: Combining social surveys and big data analyses of Twitter (SUF Edition)", https://doi.org/10.11587/OVHKTR, AUSSDA, V1, UNF:6:jPjxWXqS6RVg4uYo3Zplcw== [fileUNF] Full edition for scientific use. Our research aims to measure polarization in public opinion, combining two state-of-the-art approaches in measuring opinion - survey research and big data analytics of social media. We focus on the topic of polarization of opinions on COVID-19 and climate change and identify if and how polarization - a shift towards...
10748_da_de_v1_0.tab Sep 13, 2021 - Polarization in public opinion: Combining social surveys and big data analyses of Twitter (SUF Edition) Tabular Data - 523.2 KB - 50 Variables, 2560 Observations - UNF:6:jmLG0YIUSn6TTaUououfAQ== DataSTATA Core data file - STATA format - 50 Variables, 2560 Observations

10061_readme.pdf

Oct 8, 2021 - AUTNES Content Analysis of Party Facebook Pages 2013 (SUF edition)

Adobe PDF - 48.5 KB -

Documentation

Data curation protocol

10061_vi_en_v1_0.tab

Oct 8, 2021 - AUTNES Content Analysis of Party Facebook Pages 2013 (SUF edition)

Tabular Data - 1.9 MB - 3 Variables, 52157 Observations -

Documentation

Variable identifiers and descriptions - machine-readable

AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)

Sep 14, 2021 - AUTNES

Müller, Wolfgang C.; Bodlos, Anita; Ennser-Jedenastik, Laurenz; Graf, Elisabeth; Haselmayer, Martin; Haudum, Teresa; Huber, Lena Maria; Meyer, Thomas M.; Reidinger, Verena, 2021, "AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)", https://doi.org/10.11587/SFCAOO, AUSSDA, V1, UNF:6:7rxSZYniYODoo0eWQ8bfgw== [fileUNF]

Full edition for scientific use. The AUTNES dataset on party newspaper ads 2017 contains data on advertisements published in Austria's leading newspapers (Der Standard, Die Presse, Heute, Kleine Zeitung, Kronen Zeitung, Kurier, Österreich, Salzburger Nachrichten) within the last six weeks before the 2017 national election. The coding procedure appl...

10727_co_en_v1_0.pdf

Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)

Adobe PDF - 547.2 KB -

CodebookDocumentation

Codebook

10727_da_en_v1_0.tab

Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)

Tabular Data - 53.9 KB - 52 Variables, 274 Observations -

DataSTATA

Core data file - STATA format - 52 Variables, 274 Observations

10727_da_en_v1_0.zip

Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)

ZIP Archive - 5.8 KB -

CSVData

Core data file - compressed csv format - 52 Variables, 274 Observations

10727_da_en_v1_0.zsav

Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)

Unknown - 1.8 MB -

DataSPSS

Core data file - compressed SPSS format - 52 Variables, 274 Observations

10727_vi_en_v1_0.tab

Sep 14, 2021 - AUTNES Content Analysis of Party Newspaper Ads 2017 (SUF edition)

Tabular Data - 2.0 MB - 3 Variables, 57562 Observations -

Documentation

Variable identifiers and descriptions - machine-readable

Polarization in public opinion: Combining social surveys and big data analyses of Twitter (SUF Edition)

Sep 13, 2021 - COVID-19 Pandemic

Hadler, Markus; Klösch, Beate; Lex, Elisabeth; Reiter-Haas, Markus, 2021, "Polarization in public opinion: Combining social surveys and big data analyses of Twitter (SUF Edition)", https://doi.org/10.11587/OVHKTR, AUSSDA, V1, UNF:6:jPjxWXqS6RVg4uYo3Zplcw== [fileUNF]

Full edition for scientific use. Our research aims to measure polarization in public opinion, combining two state-of-the-art approaches in measuring opinion - survey research and big data analytics of social media. We focus on the topic of polarization of opinions on COVID-19 and climate change and identify if and how polarization - a shift towards...

10748_da_de_v1_0.tab

Sep 13, 2021 - Polarization in public opinion: Combining social surveys and big data analyses of Twitter (SUF Edition)

Tabular Data - 523.2 KB - 50 Variables, 2560 Observations -

DataSTATA

Core data file - STATA format - 50 Variables, 2560 Observations

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