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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31 to 40 of 46 Results
Jan 28, 2021
Müller, Wolfgang C.; Bodlos, Anita; Dolezal, Martin; Eder, Nikolaus; Ennser-Jedenastik, Laurenz; Kaltenegger, Matthias; Meyer, Thomas M.; Praprotnik, Katrin; Winkler, Anna Katharina, 2021, "AUTNES Content Analysis of Party Manifestos 2002 (SUF edition)", https://doi.org/10.11587/THIDUU, AUSSDA, V1, UNF:6:a4Sq7qH3IQUbdgVs+D0HBA== [fileUNF]
Full edition for scientific use. The AUTNES dataset on party manifestos covers the manifestos of the relevant parties that competed in the Austrian national elections 2002. All natural sentences within the manifestos are part of the dataset. The units of analysis are standardized...
Jan 28, 2021
Müller, Wolfgang C.; Bodlos, Anita; Dolezal, Martin; Eder, Nikolaus; Ennser-Jedenastik, Laurenz; Kaltenegger, Matthias; Meyer, Thomas M.; Praprotnik, Katrin; Winkler, Anna Katharina, 2021, "AUTNES Content Analysis of Party Manifestos 2006 (SUF edition)", https://doi.org/10.11587/XJZPCU, AUSSDA, V1, UNF:6:77INWnY0/BTZHIQbsNy6wg== [fileUNF]
Full edition for scientific use. The AUTNES dataset on party manifestos covers the manifestos of the relevant parties that competed in the Austrian national elections 2006. All natural sentences within the manifestos are part of the dataset. The units of analysis are standardized...
Jan 28, 2021
Müller, Wolfgang C.; Bodlos, Anita; Dolezal, Martin; Eder, Nikolaus; Ennser-Jedenastik, Laurenz; Kaltenegger, Matthias; Meyer, Thomas M.; Praprotnik, Katrin; Winkler, Anna Katharina, 2021, "AUTNES Content Analysis of Party Manifestos 2008 (SUF edition)", https://doi.org/10.11587/U4DWGK, AUSSDA, V1, UNF:6:iLiGDE7xtcjqSRvQ4yDTkg== [fileUNF]
Full edition for scientific use. The AUTNES dataset on party manifestos covers the manifestos of the relevant parties that competed in the Austrian national elections 2008. All natural sentences within the manifestos are part of the dataset. The units of analysis are standardized...
Jan 28, 2021
Müller, Wolfgang C.; Bodlos, Anita; Dolezal, Martin; Eder, Nikolaus; Ennser-Jedenastik, Laurenz; Kaltenegger, Matthias; Meyer, Thomas M.; Praprotnik, Katrin; Winkler, Anna Katharina, 2021, "AUTNES Content Analysis of Party Manifestos 2013 (SUF edition)", https://doi.org/10.11587/YJT5WA, AUSSDA, V1, UNF:6:iWOhIDXh6dBFX98LPU4FnA== [fileUNF]
Full edition for scientific use. The AUTNES dataset on party manifestos covers the manifestos of the relevant parties that competed in the Austrian national elections 2013. All natural sentences within the manifestos are part of the dataset. The units of analysis are standardized...
Jan 27, 2021
Müller, Wolfgang C.; Bodlos, Anita; Ennser-Jedenastik, Laurenz; Gahn, Christina; Graf, Elisabeth; Haselmayer, Martin; Haudum, Teresa; Huber, Lena Maria; Meyer, Thomas M.; Wurzer, Katharina, 2021, "AUTNES Content Analysis of Party Manifestos 2017 (SUF edition)", https://doi.org/10.11587/9LZSK5, AUSSDA, V1, UNF:6:sJ8nnBvgrK1dCf0zHFMfHg== [fileUNF]
Full edition for scientific use. The AUTNES dataset on party manifestos covers the manifestos of the relevant parties that competed in the Austrian national election 2017. All natural sentences within the manifestos are part of the dataset. The units of analysis are standardized...
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...
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...
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).
Aug 27, 2020
Wagner, Markus; Aichholzer, Julian; Eberl, Jakob-Moritz; Meyer, Thomas M.; Berk, Nicolai; Büttner, Nico; Boomgaarden, Hajo; Kritzinger, Sylvia; Müller, Wolfgang C., 2018, "AUTNES Online Panel Study 2017 (SUF edition)", https://doi.org/10.11587/I7QIYJ, AUSSDA, V4, UNF:6:qXpb3Rjb7GgLHw7J3wNrEA== [fileUNF]
Full edition for scientific use. The AUTNES Online Panel Study 2017 is a six-wave panel that focuses on the Austrian National Parliamentary Election held on 15 October 2017. This survey is part of the Austrian National Election Study (AUTNES).
Apr 24, 2020
Kritzinger, Sylvia; Aichholzer, Julian; Johann, David; Wagner, Markus; Willman, Johanna; Zeglovits, Eva, 2020, "AUTNES Post Post Election Survey 2009 (SUF edition)", https://doi.org/10.11587/QZG1XH, AUSSDA, V1, UNF:6:jzzAzzB5qT9uSsvH9nkSDQ== [fileUNF]
Full edition for scientific use. This dataset contains political preferences of Austrian citizens eligible to vote (age 18 and older) after the national parliamentary election on 28.9.2008. It was conducted in the period 6.5. – 2.7.2009 through personal interviews (CAPI). 1165 re...
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