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Non-Literal Text Reuse in Historical Texts: An Approach to Identify Reuse Transformations and its Application to Bible Reuse.

, , , , and . EMNLP, page 1849-1859. The Association for Computational Linguistics, (2016)

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Sentiment Dynamics of Success: Fractal Scaling of Story Arcs Predicts Reader Preferences., , , and . CoRR, (2021)Hybrid Language Segmentation for Historical Documents., and . CLiC-it/EVALITA, volume 1749 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)Predicting Human Metaphor Paraphrase Judgments with Deep Neural Networks., and . Fig-Lang@NAACL-HLT, page 45-55. Association for Computational Linguistics, (2018)Sentimental Matters - Predicting Literary Quality by Sentiment Analysis and Stylometric Features., , , and . WASSA@ACL, page 11-18. Association for Computational Linguistics, (2023)How Human is Machine Translationese? Comparing Human and Machine Translations of Text and Speech., , , , , and . IWSLT, page 280-290. Association for Computational Linguistics, (2020)Persistence of gender asymmetries in book reviews within and across genres., , , , and . CHR, volume 3558 of CEUR Workshop Proceedings, page 14-28. CEUR-WS.org, (2023)Some steps towards the generation of diachronic WordNets., , , and . NODALIDA, page 55-64. Linköping University Electronic Press, (2019)Measuring Translationese across Levels of Expertise: Are Professionals more Surprising than Students?, and . NoDaLiDa, page 53-63. Linköping University Electronic Press, Sweden, (2021)Dimensions of Quality: Contrasting Stylistic vs. Semantic Features for Modelling Literary Quality in 9, 000 Novels., and . RANLP, page 739-747. INCOMA Ltd., Shoumen, Bulgaria, (2023)Bigrams and BiLSTMs Two Neural Networks for Sequential Metaphor Detection., and . Fig-Lang@NAACL-HLT, page 91-101. Association for Computational Linguistics, (2018)