Call for paper

Call for papers — MeSSH 2026 Conference

Conference on methods in social sciences and humanities — 2026 edition
9 and 10 July 2026
Campus Condorcet — Centre des Colloques (Aubervilliers, France)

Digital transformations are profoundly affecting research practices in the humanities and social sciences (HSS). Massive access to heterogeneous corpora, the rise of computational methods and computing resources, the widespread use of data infrastructures, and the proliferation of collaborative tools are transforming the ways in which knowledge is captured, produced, analysed and shared. These transformations are enabling the development of new research methodologies and contributing to the development of more traditional approaches.
Organised by the Huma-Num and Progedo research infrastructures (IR*) and the Humathèque du Campus Condorcet, the ‘MeSSH 2026’ conference provides a space for discussion and reflection on all the methodological issues that are relevant to the humanities and social sciences today. It aims to bring together the entire scientific community—researchers, doctoral students, engineers, documentation and heritage professionals.

The objective of this event is twofold:

• to promote the circulation of experiences and practices between disciplines, projects and institutions;
• to contribute to the structuring of communities working on methods, tools and infrastructures in the humanities and social sciences.

 Nine themes are proposed and structure the call for contributions detailed below:

• Web data and social networks (Christine Barats, Valérie Beaudouin, Sophie Gebeil)
• Interviews and observations (Monica Heintz, Guillaume Garcia)
• Mixed methods (Cyril Benoit, Valentin Brunel)
• Digitisation, representation, simulation (Xavier Granier, Livio de Luca)
• Heritage and artistic creation (Géraldine David, Xavier Jacques-Jourion, Sara Lammens, Kim Oosterlinck, Anne-Sophie Radermecker)
• Sound, image and georeferenced data (Julien Schuh, Marion Maisonobe)
• Surveys and experiments (Pierre Mercklé, Solenne Roux)
• Statistics and causal inference (Jean Lacroix, Sophie Panel)
• Text and language (Céline Poudat, Anne-Marie Turcan)

Submission procedures
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Proposals for papers must be submitted entirely online, via the dedicated sciencesconf platform:
https://messh26.sciencesconf.org/
After logging in to the sciencesconf platform with your username and password, your proposal must include:

• a title
• an abstract (800 words max)
• your choice of one of the nine proposed themes (reassignments will be possible at a later date)
• the language of your contribution (French or English)
• 3 to 5 keywords;
• confirmation of the speakers.

Accepted proposals must submit the full text of their contribution before 1 July 2026.

Calendar

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• Submission deadline: 6 February 2026
• Notification of acceptance : 2 March 2026
• Deadline for submission of full papers : 1 July 2026
• Conference : 9–10 July 20265
  
  

Thematic calls

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Web data and social networks

The theme ‘Web data and social networks’ will welcome proposals that use digital data to address issues in the humanities and social sciences. Articles should specify the theme, theoretical framework, and research question.
They must be based on fieldwork and digital sources: data from web archives, corpora compiled by the researcher, provided that the criteria for compilation and preservation are clearly stated, data from platforms, provided that the forms of partnership are clearly stated.
The methods used to process the corpora may include:
- text mining,
- network analysis,
- image mining,
- machine learning methods (provided that an evaluation system has been planned),
- ethnographic methods.
Preference will be given to proposals that combine several categories of methods, as well as proposals that justify the use of web and/or social media data in light of the state of the art in the field being studied.

Interviews and observations

From the supposed ethnographic shift in social sciences to the more recent upheavals brought about by open science and ethical regulation of research, not to mention the development of data analysis software, so-called ‘qualitative’ research faces methodological challenges that affect several disciplinary communities whose research is based primarily on observations and interviews.
The practice of observation and interviewing has been extensively questioned from the perspective of the investigator/respondent relationship. The various sessions in this thematic area will aim to broaden this reflection by examining ‘field’ research practices from other, less explored or emerging perspectives. Discussions are invited on four issues:

1- Analysis of textual materials. The various uses that researchers make of textual tools for their analyses (i.e. CAQDAS or text analysis software – ADT), their uneven development across disciplines, and the degree of knowledge or adherence to the theoretical models embedded in these tools, which are rooted in very different disciplinary traditions, are worthy of examination. Similarly, the discrepancies between the centrality of language in certain areas of sociology and the lack of interest specifically in language in many forms of analysis, or the intrinsic limitations of using a linguistic lens in ethnology/anthropology, which focuses on the unspeakable, could also be questioned.

2 - Training in research ethics. The development of ethical regulation mechanisms for field research, which have become mandatory, raises questions about how ethics training should be conducted. How can ethics be taught, using which scenarios or practical exercises, collective or individual, and which research data, real or simulated? In the same way that teaching kits based on existing data are being developed to support the teaching of quantitative methods, can we equip survey ethics training outside of field experience? Can we move beyond training experiences that are often generalist, predominantly legal, and promote standards of good practice?

3 - Archiving and reusing survey materials. The archiving of research materials raises questions about their heritage value, but also about the distortions of the image of empirical social sciences that their heritage status may cause. What about the relative progress of social science disciplines in this regard? Does the archiving and reuse of qualitative data follow a specific path for each discipline, or are there similar patterns? Is there dialogue between disciplines, with some emerging as models? What is the relative proportion of questions about reproducibility, secondary analysis, licences and intellectual property rights, especially collective ones, concerning data within each discipline?

4 - The place of data and methods in the scientific writing phase. The development of ‘data papers’, in dedicated sections within traditional academic journals or in specialised journals (data journals), deserves to be examined. What are the possibilities for integrating qualitative data based on interviews and observation into this new editorial genre? Can both the description of the data and the survey methodology be shared? How do these ‘objects’ affect the traditional methods of scientific evaluation of articles? Do they require specific evaluation? What is the academic return on investment in writing such articles, and are they likely to disrupt the division of labour between researchers and engineers in scientific writing? 

 Proposals for papers may mainly focus on practical feedback or more general perspectives, but must be based on empirical data.

Mixed methods

Mixed methods are becoming increasingly important in the humanities and social sciences. Although they sometimes take the form of a simple juxtaposition of quantitative and qualitative data, their development opens up possibilities for greater complementarity, dialogue and combination – and therefore invites us to explicitly question how different forms of knowledge can be articulated.

This thematic area seeks to bring together contributions that exploit or question this plurality of investigative methods, whether to enrich an analysis, resolve an empirical problem, or answer the same research question by combining several methodological approaches. The call is more specifically open to two main types of contributions.

On the one hand, we welcome contributions that make concrete use of mixed methods. For example, they may combine classifications derived from qualitative work to feed into quantitative models, statistical analyses of textual materials collected using qualitative methodology, or qualitative investigations of numerical data, models or indicators produced by actors (following, for example, the model of the sociology of quantification). They may also be part of an integration approach, particularly when the combination of methods aims to resolve a causal or inferential question: for example, using large N quantitative results to identify relationships or correlations, then small N qualitative surveys to explore the underlying mechanisms; or, conversely, relying on initial qualitative work to inform the modelling or construction of quantitatively tested hypotheses.

We also welcome reflections on the appropriateness, conditions and limitations of implementing mixed methods. These proposals may take the form of feedback, critical reflections, or analyses focusing on the obstacles encountered when combining different approaches – tensions between levels of analysis, apparent contradictions between qualitative and quantitative results, difficulties of integration, epistemological issues, differentiated socialisation to methods, or institutional constraints. Papers on failures, inconclusive attempts at combination, or analyses of what does not ‘work’ in mixed methods are particularly welcome. Presentations on the methods that lend themselves best to combination (textual analysis, process tracing, Bayesian models, tooled ethnography, QCA, regressions, factorial analyses, etc.) are also encouraged.

Contributions are open to all disciplines in the humanities and social sciences, as well as interdisciplinary work (digital sciences, health, environment, political economy, education, law, etc.).

Digitalisation, representation and simulation

The thematic area ‘Digitising, Representing, Simulating: Integrated Approaches for the Humanities and Social Sciences’ aims to explore all methods used in the humanities and social sciences to document, model and experiment with the dynamics of social, cultural, material and territorial phenomena. It focuses on the complete cycle from digitisation—i.e. the production of data, its structuring (spatial, textual, visual, behavioural, etc.) and finally its immersion in models (geometric, semantic or conceptual, computational, large language models or LLM, etc.) to represent and extract underlying information, through to its use in simulations or experiments. In the so-called ‘hard’ sciences, simulations are used to model the real world and predict behaviour; in the humanities and social sciences, they also become tools for exploring, explaining and testing hypotheses, in close conjunction with data and field practices.

 This theme will welcome contributions from a variety of fields such as heritage (3D reconstruction/restitution, analysis of expert practices, documentation of material transformations, appearance, etc.), archaeology (spatial models, chrono-stratigraphy) and experimental digital archaeology (simulation of processes and techniques, etc.), geography (territorial simulation, urban evolution, etc.), history (reconstruction of processes, etc.), anthropology (modelling of interactions and gestures, etc.), economics and sociology (multi-agent models, simulations of collective behaviour, etc.), languages (notably with the impact of LLMs) and computational digital humanities (mixed models, simulations inferred from corpora, etc.).

The aim of this research area is therefore to bring together heterogeneous but convergent approaches that use digital modelling as a lever for analysis, understanding and methodological reflexivity, while questioning their epistemological foundations, limitations and collaborative implications. Particular attention will be paid to the interpretability of results. Indeed, while digital tools now facilitate the creation of data, models, classifications, etc. on a large scale, interpretability depends heavily on methodologies, particularly those used to produce the data, the conditions under which it was acquired and the modelling choices made.

Heritage and artistic creation

TBA.

Sound, image and geo-referenced data

At the stages of collecting, processing, sharing and exploiting data from research in the humanities and social sciences, sound, image and audiovisual media mobilise communities and specialist expertise (cartographers, geomaticians, signal processing specialists, art historians, archaeologists, archivists, anthropologists, architects and urban planners, etc.). Despite disciplinary differences and the varying roles these media play within different disciplines, common methodological issues (curation, querying, digitisation, enrichment, standardisation, protocol sharing, restoration, georeferencing, dating, use of AI to detect patterns and similarities) are shared across these communities. These practices raise tensions and methodological questions between ‘traditional’ approaches (formal analysis, in situ work, field surveys) and instrumental or computational methods; between attention to material objects (manuscripts, maps, films, recordings) and the processing of their digital derivatives (sound files, images, metadata).

The shift towards multimodal data encourages dialogue between these disciplines and the use of heterogeneous sources combining text, sketches, graphics, photographs, sound, video and maps. This involves both cross-referencing these sources (for example, comparing filmed interviews with written or iconographic archives) and designing methods and tools that enable several modalities to be linked to the same object of study (text/sound, image/sound, map/photograph, etc.). Open tools are being developed for the collection and processing of heterogeneous data, while data visualisation and exploration applications are being enhanced by the possibilities offered by the web and interactivity. New avenues of research are emerging for automatically aligning sound content with images (e.g. a piece of music with a score) or for jointly processing georeferenced data from sound sensors and cameras (e.g. for urban management purposes). Finally, issues of personal data protection and data ownership (copyright on audio or artistic content; respect for indigenous peoples) challenge the scientific approach and conflict with the objective of openness and reproducibility of certain analyses. In order to contribute to this dialogue, we welcome proposals on:

• On methods for collecting and capturing heterogeneous data in the field;
• On protocols for annotating, describing and entering data into sound, visual, audiovisual or multimodal corpora (choice of categories, controlled vocabulary, uncertainty);
• On the challenges of visualising and exploring heterogeneous and georeferenced data;
• On georeferencing and detecting place names in textual, iconographic or sound corpora;
• On the detection of patterns, regularities and similarities within or between textual, iconographic or audio corpora;
• On the challenges of promoting, sharing, exhibiting and disseminating audio, visual or audiovisual productions;
• On the methodological and epistemological challenges of combining ‘traditional methods’ and digital methods for the analysis of sound, image and audiovisual media (feedback, case studies, reflection on tools).

Surveys and experiments

The thematic area ‘Surveys and experiments’ welcomes papers that take stock of the state of knowledge, practices, research and innovations in the various fields of survey methodology, polling and experimentation. It thus aims to open up a space for dialogue between approaches from very different disciplines, whether these are based on the use of surveys or experiments. The main dimensions of this theme, developed below, relate as much to the collection, processing and analysis of data, whether through questionnaire surveys, experiments or a hybrid of these two methods. Questions relating to the reproducibility of data collection and/or analysis techniques are also included in this theme. Proposals may therefore fall within one or more of the following areas:

Surveys and survey theory: while in everyday language, polls usually refer to the techniques used by private polling organisations to gather opinions, in statistics the term refers to the technique of taking a small sample from a larger population that is being studied, and ‘polling theory’ refers to the field of mathematics and statistics that deals with the statistical conditions and methods governing this practice. Proposals that reflectively examine methodological advances, for example in sampling techniques, data adjustment, surveys of hard-to-reach or vulnerable populations, whether in the context of experiments or questionnaire surveys, are welcome. By extension, the methods used in quantitative surveys based on an exhaustive questioning of all individuals in the reference population are also targeted, as this population may be more or less limited in size, sometimes comprising only a few dozen individuals. From this point of view, analyses of specific samples and ‘small numbers’ statistics will also be considered with interest.

Questionnaire surveys: More generally, the first major dimension of this theme invites papers on innovations in quantitative questionnaire surveys of population samples: questionnaire design and administration, panel management, collection of specific data (interpersonal networks, prosopographic data, etc.), data quality, data processing and non-response, personal and sensitive data, anonymisation and pseudonymisation, survey ethics, etc.
Experimentation: The second dimension of this theme aims to focus attention on experimental methods. Experimental methods originated in the natural sciences in the 19th century, but have since spread to the humanities and social sciences and have long been used in psychology, economics, education sciences, sociology, etc. We welcome proposals for papers on innovations or issues of concern relating to experimental approaches in the humanities and social sciences in a very broad sense, whether in terms of context, in the laboratory or online, or experimental design (e.g. role-playing, with or without electrophysiological measurements).

Hybridisations: The research area will also welcome papers exploring data collection and analysis techniques that combine or hybridise these different methods, for example by combining questionnaires and experimentation, using quasi-experimental approaches to data analysis, resorting to quantified observation, modelling or simulation, or by examining the potential contributions of artificial intelligence in these different fields.

Statistics and causal inference

The thematic area ‘Statistics and causal inference’ aims to open an interdisciplinary dialogue on the use of statistics in the social sciences. Particular attention will be paid to the notion of causality. To this end, the thematic area welcomes proposals for papers on any work that allows for discussion on statistical methods in the social sciences. This work may be epistemological, theoretical or applied in nature. Work on the following concepts will receive particular attention:

• Epistemology of the role of statistics in the administration of evidence (particularly causal evidence) in the social sciences;
• Non-statistical approach to causality;
• Methodology of causal inference;
• Applied causal inference
• Empirical work using statistical techniques for causal identification.
• Statistical analysis in the social sciences
• Empirical work using statistical analysis.

The ‘Statistics and Causal Inference’ sessions aim to encourage interdisciplinary dialogue. Contributions from all disciplines in the humanities and social sciences are therefore welcome, as are contributions in philosophy or the sociology of science.

Text and Language

The ‘Text and Language’ theme focuses on how the creation, availability, exploration and analysis of textual data and data on the transmission of texts are transforming research questions, and on the role that digital technology plays in these processes. It thus invites joint reflection on the data, tools and interpretative frameworks that structure current research on texts and their history.
We welcome unpublished papers on digital corpora, whether on the principles of their constitution, digitisation, structuring and encoding, or on their documentation, curation and preservation according to FAIR principles.

We also encourage proposals presenting original computational methodologies for exploring these corpora, including text mining, textometry, stylometry, data annotation, automatic language processing, and visualisation tools for interpretation.
The issue of text reuse and interoperability will also be addressed.
Finally, we would like to explore, through well-informed, critical and problematised communications, the question of the use of AI on corpora of textual sources and language data, including for small corpora and languages with limited resources.