Topic Classification Term: Elections ((CESSDA Topic Classification))
Topic Classification Term: Language and linguistics ((CESSDA Topic Classification))
1 to 4 of 4 Results
Jun 7, 2022 - AUTNES
Kleinen-von Königslöw, Katharina; Haselmayer, Martin; Jacobi, Carina; Eberl, Jakob-Moritz; Vonbun, Ramona; Schönbach, Klaus; Boomgaarden, Hajo G., 2022, "AUTNES Automatic Content Analysis of the Media Coverage 2013 (SUF edition)", https://doi.org/10.11587/NJ1ZTP, AUSSDA, V1, UNF:6:SnFQ3UAAz/TAAzHaouQfDw== [fileUNF]
Full edition for scientific use. This is a dataset on the media coverage on the 2013 Austrian National Election. 43021 contributions from 61 print TV, radio and online media (selected according to various criteria to represent the Austrian media landscape as accurately as possibl... |
May 3, 2022 - AUTNES
Müller, Wolfgang C.; Bodlos, Anita; Dolezal, Martin; Eder, Nikolaus; Ennser-Jedenastik, Laurenz; Kaltenegger, Matthias; Meyer, Thomas M.; Praprotnik, Katrin; Winkler, Anna Katharina, 2022, "AUTNES Content Analysis of Party Leader Statements 2002 (SUF edition)", https://doi.org/10.11587/RYHTKW, AUSSDA, V1, UNF:6:8oSzFbs8yl2CEckCSOmMzw== [fileUNF]
Full edition for scientific use. The AUTNES coding of leader statements covers all public statements and actions of leaders of relevant parties in the six weeks before the 2002 election, as documented in Austria’s two leading quality newspapers (Der Standard and Die Presse). Lead... |
Dec 2, 2020 - AUTNES
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 - AUTNES
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... |