37.2509, Confs: 4th International Conference Data & Digital Humanities (Portugal)

[The LINGUIST List]

LINGUIST List: Vol-37-2509. Wed Jul 29 2026. ISSN: 1069 - 4875.

Subject: 37.2509, Confs: 4th International Conference Data & Digital Humanities (Portugal)

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Date: 27-Jul-2026
From: Micaela Aguiar [maguiar at letras.up.pt]
Subject: 4th International Conference Data & Digital Humanities


4th International Conference Data & Digital Humanities
Short Title: DDHUM26
Theme: Data, Science and Digital Communication: Interdisciplinary
Perspectives

Date: 26-Nov-2026 - 27-Nov-2026
Location: Braga, Portugal
Meeting URL: https://eventos.cehum.elach.uminho.pt/DDHUM2026/#en

Linguistic Field(s): Applied Linguistics; Computational Linguistics;
Discourse Analysis; General Linguistics; Text/Corpus Linguistics

DDHUM26 — 4th International Conference Data & Digital Humanities
Data, Science and Digital Communication: Interdisciplinary
Perspectives
26–27 November 2026 - University of Minho, Braga, Portugal
The 4th edition of the International Conference Data & Digital
Humanities (DDHUM26) is framed by the theme “Data, Science and Digital
Communication: Interdisciplinary Perspectives”, exploring contemporary
intersections between data practices, scientific knowledge production,
and digital communication environments.
The conference adopts an interdisciplinary perspective, bringing
together approaches from Digital Humanities, data science,
computational linguistics, communication studies, media studies,
information science, education, artificial intelligence, digital
culture, and science communication. It aims to examine how digital
methods, computational tools, communication practices, and
public-facing narratives are reshaping contemporary knowledge
ecosystems.
Contributions may focus, for example, on the following thematic axes:
1. Getting textual data
— corpora of scientific texts, including articles, abstracts,
conference papers, research reports, preprints, or science policy
documents;
— institutional repositories, digital libraries, scientific archives,
and Open Science infrastructures;
— collection of scientific texts from academic platforms, journals,
databases, institutional websites, or open archives;
— metadata, annotation, documentation, curation, and preservation of
scientific corpora;
— ethics, copyright, licences, consent, and responsible reuse of
scientific texts;
— AI-generated or AI-enriched scientific textual data, with attention
to issues of validation and traceability.
2. Finding inspiration in textual data
— computational text analysis and corpus linguistics applied to
scientific texts;
— analysis of scientific discourse, frames, argumentative strategies,
and forms of knowledge circulation;
— classification and comparison of scientific genres, such as
articles, abstracts, preprints, conference papers, reports, or
scientific press releases;
—terminology extraction, named entity recognition, and mapping of
relations between concepts, authors, institutions, disciplines, and
research objects;
— analysis of readability, clarity, accessibility, and communicative
adequacy in scientific or specialised texts;
articulation between quantitative, qualitative, and interpretive
methods in the analysis of scientific corpora;
— use of AI in the analysis, summarisation, translation,
classification, adaptation, or simplification of scientific corpora;
— human validation, explainability, and transparency in AI-assisted
corpus analysis processes;
— critical AI literacy, data literacy, authorship, academic integrity,
and scientific responsibility in the processing of scientific corpora.
3. Telling a story with textual data
— communication of results derived from scientific corpora in digital
environments;
— transformation of scientific texts into accessible content for
different audiences;
— visualisation of textual data derived from scientific corpora,
including infographics, graphical abstracts, dashboards, or concept
maps;
— digital, multimodal, and transmedia storytelling applied to the
communication of results derived from scientific corpora;
— podcasts, short videos, newsletters, threads, websites, and
platform-native formats for the popularisation of scientific content;
— translation, localisation, plain language, textual simplification,
and adaptation of scientific or specialised texts for different
audiences;
— responsible communication of corpus analysis results, with attention
to the risks of oversimplification, overinterpretation, or loss of
rigour;
— data literacy, scientific literacy, and critical AI literacy in the
mediation of scientific corpora.
Languages of Communication:
The conference accepts presentations and submissions in the following
languages:
 - English
 - Portuguese
 - Spanish
 - French
 - Italian
The final paper must be written in English.
Important Dates:
30 September 2026 — Abstract submission deadline
15 October 2026 — Notification of acceptance or rejection
15 October 2026 — Registration opens
15 November 2026 — Registration closes
26–27 November 2026 — Conference dates
30 January 2027 — Final paper submission
Abstracts must be between 250 and 400 words, excluding references, and
may be submitted in English, French, Spanish, Italian, or Portuguese.
Presentations may also be delivered in any of these five languages.
However, final papers must be submitted in English.
Proposals must be prepared in Microsoft Word (.docx) format, using the
template available here:
https://docs.google.com/document/d/12wn5t-XMaa-IG1Vd4DJI78ibCnkn16QX/edit?usp=sharing&ouid=112794293489577615973&rtpof=true&sd=true
.
To use the template, open the document and select File > Download >
Microsoft Word (.docx). Complete the downloaded document and send it
by email to ddhumconference at gmail.com.
Each accepted presentation will consist of a 20-minute presentation,
followed by 10 minutes of discussion.



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