References
- 1Antoniak, M., & Walsh, M. (2020). The crowdsourced “classics” and the revealing limits of Goodreads data. Humanities Commons.
https://hcommons.org/deposits/item/hc:31897/ - 2Bizzoni, Y., & Feldkamp, P. (2023). Comparing transformer and dictionary-based sentiment models for literary texts: Hemingway as a case-study. In 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 . - 3Chesnokova, A., Zyngier, S., Viana, V., Jandre, J., Rumbesht, A., & Ribeiro, F. (2017). Cross-cultural reader response to original and translated poetry: An empirical study in four languages. Comparative Literature Studies, 54(4), 824–849. 10.5325/complitstudies.54.4.0824
- 4China Writers Network. (2021, March 17). From “golden finger” to sweet romance: What are the differences between male and female oriented fiction?
https://www.chinawriter.com.cn/n1/2021/0317/c404027-32053332.html - 5Directive. (2019/790). Directive (EU) 2019/790 of the European Parliament and of the Council of 17 April 2019 on copyright and related rights in the Digital Single Market and amending Directives 96/9/EC and 2001/29/EC (Text with EEA relevance).
http://data.europa.eu/eli/dir/2019/790/oj - 6Elkins, K. (2022). The shapes of stories: Sentiment analysis for narrative. Cambridge University Press. 10.1017/9781009270403
- 7Evans, S., Davis, K., Evans, A., Campbell, J. A., Randall, D. P., Yin, K., & Aragon, C. (2017). More than peer production: Fanfiction communities as sites of distributed mentoring. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (pp. 259–272).
ACM . 10.1145/2998181.2998342 - 8Fischer, F., Skorinkin, D., Wessels, L., Illmer, V. J., Milling, C., Trilcke, P., & Orekhov, B. (2019).
DraCor: A multilingual corpus of dramatic texts for comparative computational analysis . In Book of Abstracts, DHd 2019. Digital Humanities im deutschsprachigen Raum. - 9Hamilton, S., & Piper, A. (2023). MultiHATHI: A complete collection of multilingual prose fiction in the HathiTrust Digital Library. Journal of Open Humanities Data, 9(3), 1–7. 10.5334/johd.95
- 10Hipson, W. E., & Mohammad, S. M. (2021). Emotion dynamics in movie dialogues. PLOS ONE, 16(9),
e0256153 . 10.1371/journal.pone.0256153 - 11Hu, Y., Underwood, T., Layne-Worthey, G., & Downie, J. S. (2023).
Cross-Cultural Classics: Preliminary Findings from Goodreads Based in the US and Douban Based in China . In DH. - 12Jockers, M. L. (2014). A novel method for detecting plot [Blog post].
http://www.matthewjockers.net/2014/06/05/a-novel-method-for-detecting-plot/ - 13Jockers, M. L. (2015). Revealing sentiment and plot arcs with the Syuzhet package [Blog post].
http://www.matthewjockers.net/2015/02/02/syuzhet/ - 14Kim, E., & Klinger, R. (2021). A survey on sentiment and emotion analysis for computational literary studies. Zeitschrift für digitale Geisteswissenschaften. 10.17175/2019_008_v2
- 15Koolen, M., Neugarten, J., & Boot, P. (2022). “This book makes me happy and sad and I love it”: A rule-based model for extracting reading impact from English book reviews. Journal of Computational Literary Studies, 1(1). 10.48694/jcls.22
- 16Liu, B. (2020). Sentiment analysis: Mining opinions, sentiments, and emotions (2nd ed.). Cambridge University Press. 10.1017/9781108639286
- 17Pianzola, F., Toccu, M., & Viviani, M. (2022). Readers’ engagement through digital social reading on Twitter: The TwLetteratura case study. Library Hi Tech, 40(5), 1305–1321. 10.1108/LHT-12-2020-0317
- 18Reagan, A. J., Mitchell, L., Kiley, D., Danforth, C. M., & Dodds, P. S. (2016). The emotional arcs of stories are dominated by six basic shapes. EPJ Data Science, 5,
Article 31 . 10.1140/epjds/s13688-016-0093-1 - 19Rebora, S., Boot, P., Pianzola, F., Gasser, B., Herrmann, J. B., Kraxenberger, M., Kuijpers, M. M., Lauer, G., Lendvai, P., Messerli, T. C., & Sorrentino, P. (2021). Digital humanities and digital social reading. Digital Scholarship in the Humanities, 36(Suppl_2), ii230–ii250. 10.1093/llc/fqab020
- 20Rohrbacher, K. (2025). Opening worlds: Narrative beginnings and the role of setting (Preprint report). Technische Universität Darmstadt. 10.26083/tuprints-00030149
- 21Schöch, C., Patraș, R., Erjavec, T., & Santos, D. (2021). Creating the European Literary Text Collection (ELTeC): Challenges and perspectives. Modern Languages Open. 10.3828/mlo.v0i0.364
- 22So, R. J., & Wezerek, G. (2020, December 11). Just how white is the book industry? The New York Times.
https://www.nytimes.com/interactive/2020/12/11/opinion/culture/diversity-publishing-industry.html - 23Viola, L. (2024). Data and workflows for multilingual digital humanities. Journal of Open Humanities Data, 10(37), 1–6. 10.5334/johd.220
- 24Wilkens, M., Evans, E. F., Soni, S., Bamman, D., & Piper, A. (2024). Small worlds: Measuring the mobility of characters in English-language fiction. Journal of Computational Literary Studies, 3(1), 1–16. 10.48694/jcls.3917
- 25Yu, Z., & Pianzola, F. (2024). Reader response across languages: A comparative sentiment analysis of Qidian and Webnovel. In W. Haverals, M. Koolen, & L. Thompson (Eds.), Proceedings of the Computational Humanities Research Conference 2024 (pp. 322–333).
CEUR Workshop Proceedings , 3834.CEUR-WS.org - 26Yu, Z., Pianzola, F., & Tatar, E. (2024). Qidian-Webnovel Corpus 110 [Data set]. DataverseNL. 10.34894/GQXX3K
- 27Zhang, Y. (2022). Cross-cultural literary comprehension: Theoretical basis and empirical research. Interkulturelles Forum der deutsch-chinesischen Gesellschaft, 1(1), 1–12. 10.1515/ifdck-2022-0005
- 28Zhang, Y., & Lauer, G. (2017). Introduction: Cross-cultural reading. Comparative Literature Studies, 54(4), 693–701. 10.5325/complitstudies.54.4.0693