Publications

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Lassche, A., Eriksen, R. S., Feldkamp, P., Heinsen, J., Baunvig, K. L. & Nielbo, K. L. (2025). Reading Beyond the Center. Modeling Book Encounters in the Danish Periphery (1800-1850). In Anthology of Computers and the Humanities (Vol. 3, pp. 95-118) https://doi.org/10.63744/YxKHrB4ZCThp

Hicke, R. M. M., Bizzoni, Y., Feldkamp, P. & Kristensen-McLachlan, R. D. (2025). Says Who? Effective Zero-Shot Annotation of Focalization. In T. Arnold, M. Fantoli & R. Ros (Eds.), Anthology of Computers and the Humanities: Computational Humanities Research 2025 (Vol. 3, pp. 738-754). Association for Computers and the Humanities. https://doi.org/10.63744/xxqzxENxsh3b

Lassen, I. M. S., Bjerring, J. C. & Nielbo, K. L. (2025). Silencing in data science practices. Big Data & Society, 12(3), 1-13. Article 20539517251365228. https://doi.org/10.1177/20539517251365228

Kardos, M., Kostkan, J., Enevoldsen, K., Vermillet, A. Q., Nielbo, K. & Rocca, R. (2025). S³ - Semantic Signal Separation. In W. Che, J. Nabende, E. Shutova & M. T. Pilehvar (Eds.), Long Papers (pp. 633-666). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2025.acl-long.32

Feldkamp, P., Bizzoni, Y., Jacobsen, M., Thomsen, M. R. & Nielbo, K. L. (2025). The Goodreads’ ›Mediocre‹: Assessing a Grey Area of Literary Judgements. In Weder Fail noch Lobgesang. Nichteindeutige Wertung von Literatur im digitalen Raum Forschungsverbund Marbach Weimar Wolfenbüttel. https://doi.org/10.17175/SB006_002

Agersnap, A., Baunvig, K. F., Schmidt, L. W., Eriksen, R. S., Bønding, E. W., Kirkegaard, T. H. & Wierød Borčak, L. (2025). The Human Touch: Leveraging HITL for Quantitative Close Reading of Historical Corpora. In DHNB 2025: Programme - Book of Abstracts (pp. 11-13) https://dhnb.eu/wp-content/uploads/2025/03/DHNB-2025_abstracts.pdf

Thunoe, M., Nielbo, K. L., Paulsen, L. B. & Yang, C. (2025). The Memeification of China’s Twitter Diplomacy, 2019–2022: Adding Memes to the Toolkit of China’s Wolf Warrior Diplomats. Global Media and Communication, 21(1), 9–30. https://doi.org/10.1177/17427665251316027

Kardos, M., Enevoldsen, K. C. & Nielbo, K. L. (2025). topicwizard -- a Modern, Model-agnostic Framework for Topic Model Visualization and Interpretation.

Mikutavicius, R., Álvarez-Tuñón, O., Brodskiy, Y. & Sarabakha, A. (2025). Towards End-to-End Underwater vSLAM Using Neural Radiance Fields. In OCEANS 2025 Brest, OCEANS 2025 IEEE. https://doi.org/10.1109/OCEANS58557.2025.11104336

Kardos, M., Enevoldsen, K., Kostkan, J., Kristensen-McLachlan, R. D. & Rocca, R. (2025). Turftopic: Topic Modelling with Contextual Representations from Sentence Transformers. The Journal of Open Source Software, 10(111), Article 8183. https://doi.org/10.21105/joss.08183

Lassche, A., Feldkamp, P., Bizzoni, Y., Baunvig, K. F. & Nielbo, K. L. (2025). Why Novels (Don't) Break Through: Dynamics of Canonicity in the Danish Modern Breakthrough (1870-1900). In Proceedings of the 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2025) (pp. 278-290) https://aclanthology.org/2025.latechclfl-1.25/

Lassche, A., Feldkamp, P., Bizzoni, Y. & Baunvig, K. F. (2025). Why Novels (Don't) Break Through: Dynamics of Canonicity in the Danish Modern Breakthrough (1870–1900). Abstract from DH Benelux 2025, Amsterdam, Netherlands. https://doi.org/10.5281/zenodo.15481901

Bizzoni, Y., Feldkamp, P., Lassen, I. M. S., Thomsen, M. R. & Nielbo, K. L. (2024). A Matter of Perspective: Building a Multi-Perspective Annotated Dataset for the Study of Literary Quality. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 789-800). European Language Resources Association (ELRA). https://aclanthology.org/2024.lrec-main.71

Bizzoni, Y. & Feldkamp, P. (2024). Below the Sea (with the Sharks): Probing Textual Features of Implicit Sentiment in a Literary Case-study. In V. Pyatkin, D. Fried, E. Stengel-Eskin, A. Liu & S. Pezzelle (Eds.), The Third Workshop on Understanding Implicit and Underspecified Language: Proceedings of the Workshop (pp. 54-61). Association for Computational Linguistics (ACL). https://aclanthology.org/2024.unimplicit-1.5

Feldkamp, P., Lassche, A., Kostkan, J., Kardos, M., Enevoldsen, K., Baunvig, K. F. & Nielbo, K. L. (2024). Canonical Status and Literary Influence: A Comparative Study of Danish Novels from the Modern Breakthrough (1870–1900). In M. Hämäläinen, E. Öhman, S. Miyagawa, K. Alnajjar & Y. Bizzoni (Eds.), NLP4DH 2024 - 4th International Conference on Natural Language Processing for Digital Humanities, Proceedings of the Conference (pp. 140-155). Association for Computational Linguistics. https://aclanthology.org/2024.nlp4dh-1.14

Feldkamp, P., Kostkan, J., Overgaard, E., Jacobsen, M. & Bizzoni, Y. (2024). Comparing Tools for Sentiment Analysis of Danish Literature from Hymns to Fairy Tales: Low-Resource Language and Domain Challenges. In O. De Clercq, V. Barriere, J. Barnes, R. Klinger, J. Sedoc & S. Tafreshi (Eds.), WASSA 2024 - 14th Workshop on Computational Approaches to Subjectivity, Sentiment, and Social Media Analysis, Proceedings of the Workshop (pp. 186-199). Association for Computational Linguistics. https://aclanthology.org/2024.wassa-1.15

Nielbo, K. L., Tilton, L. & Karsdorp, F. (2024, Nov 4). Computational Humanities Research: A new open access journal at the intersection of computational methods and the humanities.

Kristensen-McLachlan, R. D., Hicke, R. M. M., Kardos, M. & Thunø, M. (2024). Context is Key(NMF): Modelling Topical Information Dynamics in Chinese Diaspora Media. In W. Haverals, M. Koolen & L. Thompson (Eds.), Proceedings of the Computational Humanities Research Conference 2024 (Vol. 3834, pp. 829-847). CEUR-WS. https://ceur-ws.org/Vol-3834/paper49.pdf

Enevoldsen, K., Jessen, E. T. & Baglini, R. B. (2024). DANSK: Domain generalization of Danish named entity recognition. Northern European Journal of Language Technology, 10(1), 14-29. https://doi.org/10.3384/nejlt.2000-1533.2024.5249

Enevoldsen, K., Jessen, E. T. & Baglini, R. B. (2024). DANSK and DaCy 2.6. 0: Domain Generalization of Danish Named Entity Recognition. ArXiv. https://arxiv.org/pdf/2402.18209

Öhman, E., Bizzoni, Y., Moreira, P. F. & Nielbo, K. L. (2024). EmotionArcs: Emotion Arcs for 9,000 Literary Texts. In Y. Bizzoni, S. Degaetano-Ortlieb, A. Kazantseva & S. Szpakowicz (Eds.), LaTeCH-CLfL 2024 - 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Proceedings of the Workshop (pp. 51–66). Association for Computational Linguistics. https://aclanthology.org/2024.latechclfl-1.7.pdf

Charquero-Ballester, M., Walter, J. G., Rybner, A. S., Nissen, I. A., Enevoldsen, K. C. & Bechmann, A. (2024). Emotions on Twitter as crisis imprint in high-trust societies: Do ambient affiliations affect emotional expression during the pandemic? PLoS One, 19(3), Article e0296801. https://doi.org/10.1371/journal.pone.0296801

Lassen, I. M. S., Kristensen-McLachlan, R. D., Almasi, M., Enevoldsen, K. & Nielbo, K. L. (2024). Epistemic consequences of unfair tools. Digital Scholarship in the Humanities, 39(1), 198–214. https://doi.org/10.1093/llc/fqad091

Enevoldsen, K. C. (2024). Evaluating and Learning Representations for Language and Genetics. [PhD dissertation, Aarhus University].

Gao, J., Wang, F., Liu, B., Liu, F. & Nielbo, K. L. (2024). Fundamental limits to economic development in developing and underdeveloped countries imposed by global hierarchy. Structural Change and Economic Dynamics, 68, 298-312. https://doi.org/10.1016/j.strueco.2023.11.001

Bizzoni, Y., Feldkamp, P. & Nielbo, K. L. (2024). Global Coherence, Local Uncertainty: Towards a Theoretical Framework for Assessing Literary Quality. In W. Haverals, M. Koolen & L. Thompson (Eds.), Proceedings of the Computational Humanities Research Conference 2024 (Vol. 3834, pp. 172-185). Article 36 CEUR-WS.

Lassen, I. M. S., Feldkamp, P., Bizzoni, Y. & Nielbo, K. L. (2024). Literary Canonicity and Algorithmic Fairness: The Effect of Author Gender on Classification Models. CEUR Workshop Proceedings, 3834, 153-171. Article 76. https://ceur-ws.org/Vol-3834/paper76.pdf

Feldkamp, P., Bizzoni, Y., Thomsen, M. R. & Nielbo, K. L. (2024). Measuring Literary Quality. Proxies and Perspectives. Universitäts- und Landesbibliothek Darmstadt. https://doi.org/10.26083/tuprints-00027391

Feldkamp, P. & Bizzoni, Y. (2024). Modeling Multilayered Complexity in Literary Texts: A Preliminary Study. Abstract from La complexité en sciences du langage, Paris, France. https://www.sorbonne-nouvelle.fr/la-complexite-en-sciences-du-langage-862471.kjsp?RH=1236178100008

Bernstorff, M., Vistisen, S. T. & Enevoldsen, K. C. (2024). Natural language processing for electronic health records in anaesthesiology: an introduction to clinicians with recommendations and pitfalls. Journal of Clinical Monitoring and Computing, 38(2), 241-245. https://doi.org/10.1007/s10877-024-01128-3

Vrangbæk, C., Vrangbæk, E., Kardos, M., Nielbo, K. & Mortensen, J. (2024). Non-Canonical Acts and their Topical Distribution. CEUR Workshop Proceedings, 3724.

Jacobsen, M., Bizzoni, Y., Moreira, P. F. & Nielbo, K. L. (2024). Patterns of Quality: Comparing Reader Reception Across Fanfiction and Commercially Published Literature. In 2024 Computational Humanities Research Conference, CHR 2024 (Vol. 3834, pp. 718-739)

Wu, Y., Bizzoni, Y., Moreira, P. F. & Nielbo, K. L. (2024). Perplexing Canon: A study on GPT-based perplexity for canonical and non-canonical literary works. In Y. Bizzoni, S. Degaetano-Ortlieb, A. Kazantseva & S. Szpakowicz (Eds.), Proceedings of the 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL 2024) (pp. 172–184). Association for Computational Linguistics. https://aclanthology.org/2024.latechclfl-1.16.pdf

Nielbo, K. L., Karsdorp, F., Wevers, M., Lassche, A., Baglini, R. B., Kestemont, M. & Tahmasebi, N. (2024). Quantitative text analysis. Nature Reviews Methods Primers, 4(25), Article 25. https://doi.org/10.1038/s43586-024-00302-w

Bizzoni, Y. & Feldkamp, P. (2024). Sentiment Analysis for Literary Texts: Hemingway as a Case-study. Journal of Data Mining & Digital Humanities, NLP4DH, Article 13155. https://doi.org/10.46298/jdmdh.13155

Feldkamp, P., Overgaard, E. L., Nielbo, K. L. & Bizzoni, Y. (2024). Sentiment Below the Surface: Omissive and Evocative Strategies in Literature and Beyond. In Computaitonal Humanities Research 2024: Proceedings of the Computational Humanities Research Conference 2024 (Vol. 3834, pp. 681-706). Article 98 https://ceur-ws.org/Vol-3834/paper98.pdf

Kardos, M., Kostkan, J., Vermillet, A.-Q., Nielbo, K., Enevoldsen, K. & Rocca, R. (2024). S³ – Semantic Signal Separation.

Thunø, M. & Nielbo, K. L. (2024). The Initial Digitalization of Chinese Diplomacy (2019–2021): Establishing Global Communication Networks on Twitter. Journal of Contemporary China, 33(146), 244-266. https://doi.org/10.1080/10670564.2023.2195811

Enevoldsen, K., Kardos, M., Muennighoff, N. & Nielbo, K. L. (2024). The Scandinavian Embedding Benchmarks: Evaluating Multilingual and Monolingual Text Embedding for Scandinavian languages. Advances in Neural Information Processing Systems, 37.

Lindhardt Overgaard, E., Feldkamp, P. & Bizzoni, Y. (2024). Towards a GoldenHymns Dataset for Studying Diachronic Trends in 19th Century Danish Religious Hymns. In N. Tahmasebi, S. Montariol, A. Kutuzov, D. Alfter, F. Periti, P. Cassotti & N. Huebscher (Eds.), LChange 2024 - 5th International Workshop on Computational Approaches to Historical Language Change 2024, Proceedings of the Workshop (pp. 55-61). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.lchange-1.6

Elbæk, C. T., Aarøe, L., Otterbring, T., Hochman, G., Baskakovs, A. & Mitkidis, P. (2023). A scarcity mindset does not influence economic cheating across or between social classes. Abstract from IAREP-SABE International Conference, Nice, France.

Baunvig, K. F. & Nielbo, K. L. (2023). Benign Structures: The Worldview of Danish National Poet, Pastor, and Politician N.F.S. Grundtvig (1783-1872). In S. Gilbert & A. Rockenberger (Eds.), Book of Abstracts: Sustainability: Environment, Community, Data (pp. 9-11). Oslo Universitet.

Baunvig, K. F. & Nielbo, K. L. (2023). Benign Structures: The Worldview of Danish NationalPoet, Pastor, and Politician N.F.S. Grundtvig (1783-1872). In A. Rockenberger, J. Tiemann & S. Gilbert (Eds.), Conference Proceedings : DHNB2023 (pp. 1-10). Article 1 Universitetsforlaget, Oslo. https://doi.org/10.5617/dhnbpub.10646

Kristensen-McLachlan, R. D., Canavan, M., Kardos, M., Jacobsen, M. & Aarøe, L. (2023). Chatbots Are Not Reliable Text Annotators. arxiv.org. https://doi.org/10.48550/arXiv.2311.05769

Bizzoni, Y. & Feldkamp, P. (2023). Comparing Transformer and Dictionary-based Sentiment Models for Literary Texts: Hemingway as a Case-study. In M. Hämäläinen, E. Öhman, F. Pirinen, K. Alnajjar, S. Miyagawa, Y. Bizzoni, N. Partanen & J. Rueter (Eds.), Proceedings of the Joint 3rd International Conference on Natural Language Processing for Digital Humanities and 8th International Workshop on Computational Linguistics for Uralic Languages (pp. 219-228). Association for Computational Linguistics. https://aclanthology.org/2023.nlp4dh-1.25

Enevoldsen, K., Hansen, L., Nielsen, D. S., Egebæk, R., Holm, S., Nielsen, M. C., Bernstorff, M., Larsen, R., Jørgensen, P. B., Højmark-Bertelsen, M., Vahlstrup, P. B., Møldrup-Dalum, P. & Nielbo, K. L. (2023). Danish Foundation Models: Danish Foundation Models. ArXiv. https://arxiv.org/abs/2311.07264

Kolding, S., Nymann, K., Hansen, I. B., Enevoldsen, K. & Kristensen-McLachlan, R. D. (2023). DanSumT5: Automatic Abstractive Summarization for Danish. In T. Alumäe & M. Fishel (Eds.), Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa) (pp. 248-264). Tartu University Press. https://aclanthology.org/2023.nodalida-1.25/

Lassen, I. M. S., Almasi, M., Enevoldsen, K. & Kristensen-McLachlan, R. D. (2023). Detecting intersectionality in NER models: A data-driven approach. In EACL 2023 - 7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, Proceedings of LaTeCH-CLfL 2023 (pp. 116-127). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.latechclfl-1.13

Feldkamp, P. & Bizzoni, Y. (2023). Dimensions of Quality: Contrasting Stylistic vs. Semantic Features for Modelling Literary Quality in 9,000 Novels. In G. Angelova, M. Kunilovskaya & R. Mitkov (Eds.), International Conference Recent Advances in Natural Language Processing, RANLP 2023 (pp. 739-747). Association for Computational Linguistics. https://doi.org/10.26615/978-954-452-092-2_080

Wevers, M. & Nielbo, K. L. (2023). Embed, detect and describe: A framework for examining events in complex sociocultural and historical data. Abstract from CUDAN 2023, Tallinn, Estonia. https://cudan.tlu.ee/conference/CUDAN2023-abstract-21.pdf

Displaying results 51 to 100 out of 260

Revised 30.08.2023