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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 6 7 8 9 10...18 Hits 101 – 120 of 360 101 Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2019 BASE Show details 102 SenZi: A sentiment analysis lexicon for the latinised Arabic (Arabizi) Tobaili, Taha; Fernández, Miriam; Alani, Harith. - : INCOMA, 2019 BASE Show details 103 Do we really need fully unsupervised cross-lingual embeddings? Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : Association for Computational Linguistics, 2019 BASE Show details 104 Are we consistently biased? Multidimensional analysis of biases in distributional word vectors Lauscher, Anne; Glavaš, Goran. - : Association for Computational Linguistics, 2019 BASE Show details 105 Knowledge-intensive, high-performance relation extraction ... : Wissensintensive, hochperformante Relationsextraktion ... Krause, Sebastian. - : Technische Universität Berlin, 2018 BASE Show details 106 Automatic glossary term extraction from large-scale requirements specifications ... Gemkow, Tim; Conzelmann, Miro; Hartig, Kerstin. - : Technische Universität Berlin, 2018 BASE Show details 107 An Evaluation of Lexicon-based Sentiment Analysis Techniques for the Plays of Gotthold Ephraim Lessing ... Schmidt, Thomas; Burghardt, Manuel. - : Universität Regensburg, 2018 BASE Show details 108 An Evaluation of Lexicon-based Sentiment Analysis Techniques for the Plays of Gotthold Ephraim Lessing ... Schmidt, Thomas; Burghardt, Manuel. - : Universität Regensburg, 2018 BASE Show details 109 An Evaluation of Lexicon-based Sentiment Analysis Techniques for the Plays of Gotthold Ephraim Lessing Schmidt, Thomas; Burghardt, Manuel. - 2018 BASE Show details 110 An Evaluation of Lexicon-based Sentiment Analysis Techniques for the Plays of Gotthold Ephraim Lessing Schmidt, Thomas; Burghardt, Manuel. - 2018 BASE Show details 111 An Evaluation of Lexicon-based Sentiment Analysis Techniques for the Plays of Gotthold Ephraim Lessing Schmidt, Thomas; Burghardt, Manuel. - : Association for Computational Linguistics, 2018 BASE Show details 112 „Kann man denn auch nicht lachend sehr ernsthaft sein?" – Zum Einsatz von Sentiment Analyse-Verfahren für die quantitative Untersuchung von Lessings Dramen Schmidt, Thomas; Burghardt, Manuel; Dennerlein, Katrin. - : Universitäts- und Stadtbibliothek Köln, 2018 BASE Show details 113 Herausforderungen für Sentiment Analysis-Verfahren bei literarischen Texten Schmidt, Thomas; Burghardt, Manuel; Wolff, Christian. - : Gesellschaft für Informatik e.V., 2018 BASE Show details 114 Toward a Tool for Sentiment Analysis for German Historic Plays Schmidt, Thomas; Burghardt, Manuel. - : Laboratoire laussannois d'informatique et statistique textuelle, 2018 BASE Show details 115 Karel relearns C. Teaching good software engineering practices in CS1 with Karel the Robot Heckner, Markus; Bazo, Alexander; Wolff, Christian. - : IEEE, 2018 BASE Show details 116 Sentiment Annotation of Historic German Plays: An Empirical Study on Annotation Behavior Schmidt, Thomas; Burghardt, Manuel; Dennerlein, Katrin. - 2018 BASE Show details 117 Sentiment Annotation of Historic German Plays: An Empirical Study on Annotation Behavior Schmidt, Thomas; Burghardt, Manuel; Dennerlein, Katrin. - 2018 Abstract: We present results of a sentiment annotation study in the context of historical German plays. Our annotation corpus consists of 200 representative speeches from the German playwright Gotthold Ephraim Lessing. Six annotators, five non-experts and one expert in the domain, annotated the speeches according to different sentiment annotation schemes. They had to annotate the differentiated polarity (very negative, negative, neutral, mixed, positive, very positive), the binary polarity (positive/negative) and the occurrence of eight basic emotions. After the annotation, the participants completed a questionnaire about their experience of the annotation process; additional feedback was gathered in a closing interview. Analysis of the annotations shows that the agreement among annotators ranges from low to mediocre. The non-expert annotators perceive the task as very challenging and report different problems in understanding the language and the context. Although fewer problems occur for the expert annotator, we cannot find any differences in the agreement levels among non-experts and between the expert and the non-experts. At the end of the paper, we discuss the implications of this study and future research plans for this area. Keyword: 004 Informatik; 430 Deutsch; 830 Deutsche Literatur; ddc:004; ddc:430; ddc:830 URL: https://epub.uni-regensburg.de/43701/ http://ceur-ws.org/Vol-2155/schmidt.pdf https://epub.uni-regensburg.de/43701/1/Schmidt%20et%20al.%20%282018%29%20-%20SentimentAnnotation.pdf BASE Hide details 118 Deep instantiation Atkinson, Colin; Kühne, Thomas. - : Springer, 2018 BASE Show details 119 ArguminSci: a tool for analyzing argumentation and rhetorical aspects in scientific writing Glavaš, Goran; Lauscher, Anne; Eckert, Kai. - : Association for Computational Linguistics, 2018 BASE Show details 120 A neural autoencoder approach for document ranking and query refinement in pharmacogenomic information retrieval Broscheit, Samuel; Pfeiffer, Jonas; Gemulla, Rainer. - : Association for Computational Linguistics, 2018 BASE Show details Page: 1 2 3 4 5 6 7 8 9 10...18

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