34.3089, Calls: The 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

[The LINGUIST List]

LINGUIST List: Vol-34-3089. Wed Oct 18 2023. ISSN: 1069 - 4875.

Subject: 34.3089, Calls: The 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

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Date: 17-Oct-2023
From: Anna Kazantseva [latech-clfl at googlegroups.com]
Subject: The 8th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature


Full Title: The 8th Joint SIGHUM Workshop on Computational Linguistics
for Cultural Heritage, Social Sciences, Humanities and Literature
Short Title: LaTeCH-CLfL 2024

Date: 22-Mar-2024 - 23-Mar-2024
Location: St. Julian's, Malta
Contact Person: Anna Kazantseva
Meeting Email: latech-clfl at googlegroups.com
Web Site: https://sighum.wordpress.com/latech-clfl-2024/

Linguistic Field(s): Applied Linguistics; Computational Linguistics;
Ling & Literature; Text/Corpus Linguistics

Call Deadline: 18-Dec-2023

Meeting Description:

LaTeCH-CLfL 2024 is the eighth in a series of meetings for NLP
researchers who work with data from the broadly understood arts,
humanities and social sciences, and for specialists in those
disciplines who apply NLP techniques in their work. The workshop
continues a long tradition of annual meetings. The SIGHUM Workshops on
Language Technology for Cultural Heritage, Social Sciences, and
Humanities (LaTeCH) ran ten times in 2007-2016. The five Workshops on
Computational Linguistics for Literature (CLfL) took place in
2012-2016. The first seven joint workshops (LaTeCH-CLfL) were held in
2017-2023.

Call for Papers:

In the Humanities, Social Sciences, Cultural Heritage and literary
communities, there is increasing interest in, and demand for, NLP
methods for semantic and structural annotation, intelligent linking,
discovery, querying, cleaning and visualization of both primary and
secondary data. This is even true of primarily non-textual
collections, given that text is also the pervasive medium for
metadata. Such applications pose new challenges for NLP research:
noisy, non-standard textual or multi-modal input, historical
languages, vague research concepts, multilingual parts within one
document, and so no. Digital resources often have insufficient
coverage; resource-intensive methods require (semi-)automatic
processing tools and domain adaptation, or intense manual effort
(e.g., annotation).

Literary texts bring their own problems, because navigating this form
of creative expression requires more than the typical
information-seeking tools. Examples of advanced tasks include the
study of literature of a certain period, author or sub-genre,
recognition of certain literary devices, or quantitative analysis of
poetry.

NLP methods applied in this context not only need to achieve high
performance, but are often applied as a first step in research or
scholarly workflow. That is why it is crucial to interpret model
results properly; model interpretability might be more important than
raw performance scores, depending on the context.


Topics of interest include, but are not limited to, the following:

    •    adaptation of NLP tools to Cultural Heritage, Social
Sciences, Humanities and literature;
    •    automatic error detection and cleaning of textual data;
    •    complex annotation schemas, tools and interfaces;
    •    creation (fully- or semi-automatic) of semantic resources;
    •    creation and analysis of social networks of literary
characters;
    •    discourse and narrative analysis/modelling, notably in
literature;
    •    emotion analysis for the humanities and for literature;
    •    generation of literary narrative, dialogue or poetry;
    •    identification and analysis of literary genres;
    •    interpretability of large language models output for
DH-related tasks (explainable AI);
    •    linking and retrieving information from different sources,
media, and domains;
    •    low-resource and historical language processing;
    •    modelling dialogue literary style for generation;
    •    modelling of information and knowledge in the Humanities,
Social Sciences, and Cultural Heritage;
    •    profiling and authorship attribution;
    •    search for scientific and/or scholarly literature;
    •    work with linguistic variation and non-standard or historical
use of language.

Information for authors

We invite papers on original, unpublished work in the topic areas of
the workshop. In addition to long papers, we will consider short
papers and system descriptions (demos). We also welcome position
papers.

    •    Long papers, presenting completed work, may consist of up to
eight (8) pages of content plus additional pages of references (just
two if possible -:). The final camera-ready versions of accepted long
papers will be given one additional page of content (up to 9 pages) so
that reviewers’ comments can be taken into account.
    •    A short paper / demo presenting work in progress, or the
description of a system, and may consist of up to four (4) pages of
content plus additional pages of references (one if you can). Upon
acceptance, short papers will be given five (5) content pages in the
proceedings.
    •    A position paper — clearly marked as such — should not exceed
eight (8) pages including references.

All submissions are to use the EACL stylesheets (for LaTeX / Overleaf
and MS Word); there will be a link soon (we hope) but last year's
https://2023.eacl.org/calls/styles is a good guess. Papers should be
submitted electronically, only in PDF.



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