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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 5...8 Hits 1 – 20 of 151 1 Coreference in Universal Dependencies 1.0 (CorefUD 1.0) Nedoluzhko, Anna; Novák, Michal; Popel, Martin. - : Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL), 2022 BASE Show details 2 German Climate Change Tweet Corpus (GerCCT) ... Schaefer, Robin; Stede, Manfred. - : Zenodo, 2022 BASE Show details 3 German Climate Change Tweet Corpus (GerCCT) ... Schaefer, Robin; Stede, Manfred. - : Zenodo, 2022 BASE Show details 4 Lexica corpus (v2.0) ... Hewett, Freya; Stede, Manfred. - : Zenodo, 2022 BASE Show details 5 Lexica corpus (v2.0) ... Hewett, Freya; Stede, Manfred. - : Zenodo, 2022 BASE Show details 6 Shallow discourse parsing for German Bourgonje, Peter [Verfasser]; Stede, Manfred [Akademischer Betreuer]. - Potsdam : Universität Potsdam, 2021 DNB Subject Category Language Show details 7 Shallow discourse parsing for German Stede, Manfred (Akademischer Betreuer); Bourgonje, Peter; Kosseim, Leila (Akademischer Betreuer). - Potsdam, 2021 BLLDB UB Frankfurt Linguistik Show details 8 Topics and subjects in German newspaper editorials: a corpus study Bourgonje, Peter; Stede, Manfred In: Deutsche Gesellschaft für Sprachwissenschaft / Jahrestagung <39., 2017, Saarbrücken>. Information structuring in discourse. - Leiden : Brill (2021), 86-111 BLLDB Show details 9 Penn Discourse Treebank Version 2.0 - German Translation Sluyter-Gaethje, Henny; Bourgonje, Peter; Stede, Manfred. - : Linguistic Data Consortium, 2021. : https://www.ldc.upenn.edu, 2021 BASE Show details 10 Penn Discourse Treebank Version 2.0 - German Translation ... Sluyter-Gaethje, Henny; Bourgonje, Peter; Stede, Manfred. - : Linguistic Data Consortium, 2021 BASE Show details 11 Lexica corpus ... Hewett, Freya; Stede, Manfred. - : Zenodo, 2021 BASE Show details 12 Modeling Incoherent Discourse in Non-Affective Psychosis ... Just, Sandra A.; Haegert, Erik; Kořánová, Nora. - : Charité - Universitätsmedizin Berlin, 2020 BASE Show details 13 Comparing decoding mechanisms for parsing argumentative structures ... Afantenos, Stergos; Peldszus, Andreas; Stede, Manfred. - : Universität Potsdam, 2020 BASE Show details 14 Annotation and Detection of Arguments in Tweets ... The 28th International Conference on Computational Linguistics 2020; Schaefer, Robin; Stede, Manfred. - : Underline Science Inc., 2020 BASE Show details 15 Exploiting a lexical resource for discourse connective disambiguation in German ... The 28th International Conference on Computational Linguistics 2020; Bourgonje, Peter; Stede, Manfred. - : Underline Science Inc., 2020 BASE Show details 16 Variation in Coreference Strategies across Genres and Production Media ... The 28th International Conference on Computational Linguistics 2020; Aktas, Berfin; Stede, Manfred. - : Underline Science Inc., 2020 BASE Show details 17 Modeling Incoherent Discourse in Non-Affective Psychosis Just, Sandra A.; Haegert, Erik; Kořánová, Nora; Bröcker, Anna-Lena; Nenchev, Ivan; Funcke, Jakob; Heinz, Andreas; Bermpohl, Felix; Stede, Manfred; Montag, Christiane In: Front Psychiatry (2020) Abstract: BACKGROUND: Computational linguistic methodology allows quantification of speech abnormalities in non-affective psychosis. For this patient group, incoherent speech has long been described as a symptom of formal thought disorder. Our study is an interdisciplinary attempt at developing a model of incoherence in non-affective psychosis, informed by computational linguistic methodology as well as psychiatric research, which both conceptualize incoherence as associative loosening. The primary aim of this pilot study was methodological: to validate the model against clinical data and reduce bias in automated coherence analysis. METHODS: Speech samples were obtained from patients with a diagnosis of schizophrenia or schizoaffective disorder, who were divided into two groups of n = 20 subjects each, based on different clinical ratings of positive formal thought disorder, and n = 20 healthy control subjects. RESULTS: Coherence metrics that were automatically derived from interview transcripts significantly predicted clinical ratings of thought disorder. Significant results from multinomial regression analysis revealed that group membership (controls vs. patients with vs. without formal thought disorder) could be predicted based on automated coherence analysis when bias was considered. Further improvement of the regression model was reached by including variables that psychiatric research has shown to inform clinical diagnostics of positive formal thought disorder. CONCLUSIONS: Automated coherence analysis may capture different features of incoherent speech than clinical ratings of formal thought disorder. Models of incoherence in non-affective psychosis should include automatically derived coherence metrics as well as lexical and syntactic features that influence the comprehensibility of speech. Keyword: Psychiatry URL: https://doi.org/10.3389/fpsyt.2020.00846 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7466436/ BASE Hide details 18 Comparing decoding mechanisms for parsing argumentative structures Afantenos, Stergos; Peldszus, Andreas (Dr.); Stede, Manfred (Prof. Dr.). - 2020 BASE Show details 19 Of trees and birds : a Festschrift for Gisbert Fanselow Rauh, Gisa Verfasser]. - Potsdam : Universitätsverlag Potsdam, 2019 DNB Subject Category Language Show details 20 Sentiment analysis of German Twitter Sidarenka, Uladzimir [Verfasser]; Stede, Manfred [Akademischer Betreuer]; Eisenstein, Jacob [Gutachter]. - Potsdam : Universität Potsdam, 2019 DNB Subject Category Language Show details Page: 1 2 3 4 5...8

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