HummeL: - Humanities meets Learning -

Challenges for Computational Literary Studies

Workshop at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2019)

Call for Papers

Call for Papers

Digital Humanities have since their beginning in the 1940s adapted methods from computer science. In recent years the time span between invention in computer science and adaption in Digital Humanities has been reduced dramatically and today applications of ‘traditional’ machine learning and deep learning can be found in many DH papers. Nevertheless, direct exchange between researchers in machine learning and in the digital humanities is still rare. In this workshop, we want to bring together both communities and encourage cooperation between researchers from machine learning, natural language processing and digital humanities.

One of the primary goals in the Digital Humanities is the analysis of literary fiction by computational means. This workshop puts a special focus on the development and application of methods in Natural Language Processing in combination with Machine Learning to literary texts. While many of the tasks needed to achieve this goal are also found in other areas of NLP research, literary texts often provide an exceptionally challenging domain for multiple reasons. We intend to provide a forum for the exchange between researchers from machine learning and digital humanities, where these challenges can be addressed together. We believe that, in many cases, the specific challenges posed by literary texts can only be overcome by integrating the domain knowledge of (digital) humanists into machine learning methods.

Possible topics include, but are not limited to:

  • NLP to support the analysis of long text
  • Modeling character constellation with NLP and ML
  • Sentiment analysis for literature
  • Analysis of emotional states of characters
  • Coreference resolution for long documents
  • Analysis of indirect characterisation
  • Dealing with semantic change in historical texts
  • Dealing with dialect in texts
  • Social network extraction from text
  • Social network analysis from text
  • Analysis of character relations
  • Machine Learning for analysis of plot
  • Text generation of long and complex texts
  • Extraction and use of weak labels
  • Transfer learning to deal with few labeled information
  • Modeling literary text with deep learning
  • Knowledge representation for literary (long) texts
  • Integrating domain knowledge about literature into machine learning methods


Electronic submissions will be handled via Easychair.

Full submissions will be accepted until 14. June 2019

Late breaking submissions will be accepted until ?

Papers must be written in English and formatted according to the Springer Lecture Notes in Computer Science (LNCS) guidelines. Authors should consult Springer's authors' guidelines and use their proceedings templates, either for LaTeX or for Word, for the preparation of their papers. Springer encourages authors to include their ORCIDs in their papers. In addition, the corresponding author of each paper, acting on behalf of all of the authors of that paper, must complete and sign a Consent-to-Publish form. By signing this form the copyright for their paper is transferred to Springer.

The required length of a paper is 12-16 pages in LNCS format, i.e., the ECML PKDD 2019 submission format. Overlength papers will be rejected without review (papers with smaller page margins and font sizes than specified in the author instructions and set in the style files will also be treated as overlength).

In addition to that we encourage the submission of late breaking research results with up to four pages length.

Accepted papers will be published as workshop proceedings by Springer as part of the series Lecture Notes in Computer Science. The proceedings of the past ECML-PKDD Workshops are available through SpringerLink.

Important Dates

Paper Submission Deadline: 14. June 2019
Paper Acceptance Notification: 12. July 2019
Camera Ready Paper Submission: 26. July 2019
Late Breaking Submission Deadline: ?
Late Breaking Acceptance Notification: ?
Camera Ready Late Breaking Submission: ?

Keynote Speakers

Two keynotes from the field of Maschine Learning and Computational Literary Studies are planned. Speakers will be announced soon.


Zentrales Hörsaal und Seminargebäude Z6, Campus Hubland Süd, Würzburg
Größere Karte anzeigen

Futher details at ECML-PKDD Homepage