21 to 30 of 63 Results
Sep 27, 2019
Data publications from the Institute of Medical Informatics |
Sep 9, 2019 - AWI Experimental Economics
Nikiforakis, Nikos; Oechssler, Jörg; Shah, Anvar, 2019, "Managerial bonuses and subordinate mistreatment [Dataset]", https://doi.org/10.11588/data/876SOV, heiDATA, V1, UNF:6:rgdksaMzfE0dDvw+toLLbg== [fileUNF]
Can performance bonuses increase the likelihood that managers coerce their subordinates into exerting high levels of effort when doing so promotes neither efficiency nor equity? We consider a laboratory setting in which managers compete to obtain a large bonus at the end of the e... |
Wiegand, Michael; Bocionek, Christine; Ruppenhofer, Josef, 2019, "Sentiment Compound Data (DE)", https://doi.org/10.11588/data/LSTRK3, heiDATA, V1
This dataset contains gold standards that are required for building a classifier that automatically extracts opinion (noun) compounds. |
Sep 5, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael; Ruppenhofer, Josef; Schulder, Marc, 2019, "Sentiment View Lexicon (EN)", https://doi.org/10.11588/data/2JK48O, heiDATA, V1
This gold standard contains sentiment expressions (verbs, nouns and adjectives) that have been annotated according to their (prior) sentiment view. Each sentiment expression is labelled either as actor or speaker view. |
Sep 2, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael, 2019, "GermEval-2018 Corpus (DE)", https://doi.org/10.11588/data/0B5VML, heiDATA, V1
This dataset comprises the training and test data (German tweets) from the GermEval 2018 Shared on Offensive Language Detection. |
Sep 2, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael, 2019, "Lexicon of Abusive Words (EN)", https://doi.org/10.11588/data/MKPEYV, heiDATA, V1
This goldstandard contains a bootstrapped lexicon of abusive words. The lexicon comprises a large set of English negative polar expressions annotated as either abusive or not. |
Sep 2, 2019 - Empirical Linguistics and Computational Language Modeling (LiMo)
Wiegand, Michael, 2019, "Opinion role extractor", https://doi.org/10.11588/data/3W7AQP, heiDATA, V1
System for the Extraction of Subjective Expressions, Sentiment Sources and Sentiment Targets from German Text |
Sep 2, 2019 - Heidelberg University Language and Cognition Lab
Gerwien, Johannes, 2019, "The interpretation and prediction of event participants in Mandarin verb-final active and passive sentences [Dataset]", https://doi.org/10.11588/data/L7QPUY, heiDATA, V1, UNF:6:Gpy3ySsey0gDHrTBkgp1Bg== [fileUNF]
This data set contains eye tracking data collected with an SMI RED 500 eye tracking system. The experimental design, elicitation method, coding, and criteria for excluding/including data are documented in the article: Gerwien, J. (2019) "The interpretation and prediction of event... |
Sep 2, 2019 - AWI Experimental Economics
Oechssler, Jörg; Rau, Hannes; Roomets, Alex, 2019, "Hedging, ambiguity, and the reversal of order axiom [Dataset]", https://doi.org/10.11588/data/1XDKHZ, heiDATA, V1, UNF:6:c8rHrHnmCxS3BC4O6euGVQ== [fileUNF]
We ran experiments that gave subjects a straight-forward and simple opportunity to hedge away ambiguity in an Ellsberg-style experiment. Subjects had to make bets on the combined outcomes of a fair coin and a draw from an ambiguous urn. By modifying the timing of the draw, coin f... |
Roxburgh, Marcus; Olli, Maarja, 2019, "Eyes to the North: a multi-element analysis of copper-alloy eye brooches in the eastern Baltic, produced during the Roman Iron Age [Supplement]", https://doi.org/10.11588/data/7WOCTK, heiDATA, V1, UNF:6:EnP0e/xxKuwYHp2brVn3sw== [fileUNF]
Roman Iron Age. Their forms bear strong similarities to those found much further south in Germania and the northern Roman provinces, leading to the conclusion that they originally arrived in the region as imports, perhaps by sea from an as yet undiscovered production centre in an... |
