DH2024 Workshop – Computational Literary Studies: How To Do Research Responsibly (CfP) 

In the context of the DH2024 Conference “Reinvention & Responsibility” (https://dh2024.adho.org/), the SIG-DLS is organizing a pre-conference workshop entitled “Computational Literary Studies: How To Do Research Responsibly”

The overarching goal is to present, promote, and showcase a subfield of DH that has recently reached — or seems to have reached — a critical point of its maturity. Known under the name of Computational Literary Studies, Digital Literary Studies, or Cultural Analytics, the field primarily revolves around computer-assisted analysis of literary sources. It was commenced by the groundbreaking initiative SIG-DLS (https://dls.hypotheses.org/), and then further developed by a few other endeavors, e.g. the CLS Priority Programme founded by DFG (https://dfg-spp-cls.github.io/), the JCLS journal (https://jcls.io/), the CCLS annual conference (https://jcls.io/site/conference/), the Journal of Cultural Analytics (https://culturalanalytics.org/), the CHR annual conference (https://computational-humanities-research.org/), the COST Action Distant Reading (https://www.distant-reading.net/), and the CLS INFRA project founded by Horizon2020 (https://clsinfra.io/). 

The idea behind the workshop is to consolidate the already existing initiatives, and to share experiences between projects, centers, and scholars involved in DLS/CLS. The workshop program will be composed by a combination of invited talks, demo sessions, and lightning talks. 

With this Call, we are inviting submissions for lightning talks (max. 5 minutes) on ongoing projects, research ideas, and infrastructures in DLS/CLS. Please send a 250-word abstract to simone.rebora@univr.it by 15 May 2024. Proposals will be evaluated by the organizing committee and notifications sent by 30 May 2024.

Organizing committee

Maciej Eder (CLS-Infra)
Joanna Byszuk (CLS-Infra and SIG-DLS)
Simone Rebora (SIG-DLS)
Berenike Herrmann (SIG-DLS)
Suzanne Mpouli (SIG-DLS)
Pablo Ruiz Fabo (SIG-DLS)