Religion, Activism, and Computational Approaches: Interview with Tereza Menšíková

26 Jun 2026 Natálie Čornyjová

The center’s thematic scope is very broad. Some projects focus on historical research, such as Professor David Zbíral’s ERC project DISSINET, which models the issue of heresy based on extensive historical sources. A number of other projects examine, for example, the spread of Roman religious cults (the new SIPROME project), population migration, or changes in religious life in the past.

The common thread among these projects is the use of approaches such as network analysis, geographic modeling, computational text analysis, and work with large language models.

CEDRR thus serves as a space where the humanities intersect with computational approaches and where new methodological approaches are emerging that would not have been possible just a few years ago.

What does digital technology allow religious studies to research today? Has it transformed the field of research itself in any way?

Digital tools are used today in history, archaeology, psychology, sociology, and anthropology. Their great benefit lies in the fact that they allow us to work with volumes of data that would be impossible to analyze manually.

In the digital humanities, the term distant reading is used in this context. Using computational methods, we can identify patterns and connections that traditional methods of qualitative coding (such as conventional “close reading”) cannot capture.

In religious studies, this means the ability to link various types of data—such as texts, information from databases, and archaeological findings, including their metadata—and to track how religious traditions, their roles, and their influence in society spread, transformed, or disappeared. A similar approach can be taken when studying the present, for example, by combining data from social media, sociological surveys, or economic statistics. This allows us to gain a more comprehensive picture of how religion is connected to our political, economic, and social lives and how it is itself influenced by the broader environment and its changes.

How exactly do you work with online data, and how did you select the sources you analyze?

I analyze activist blogs associated with anti-caste organizations in India. These are texts in which the authors articulate their ideas about the social, religious, or political structure of society and propose ways to bring about change.

I work with corpora containing thousands of texts and also analyze their metadata—for example, information about the authors, their geographic origins, or their ties to organizations. This allows me to track, for instance, regional differences in topics and arguments and how they change over time.

The selection of sources is related to the fact that the internet plays a crucial role in Dalit and Bahujan movements. Many activists use the online environment as one of the few spaces where they can publicly express their views. Furthermore, English serves as a common language across regions, which has led to the emergence of extensive blogging platforms and media outlets that today represent the main information hubs for anti-caste activism. My research focuses specifically on their content.

Given the volume of data, I use Python or R and work in the RStudio environment or with other tools designed for analyzing large datasets.

What role does network analysis play in your research?

I use it partly as a supplementary tool. It helps me track how certain religious concepts are linked to emotions, political topics, or sources in citation networks.

It also allows me to map relationships between authors and organizations and to track the emergence of collaboration among activist groups. However, it is not the main focus of my work; rather, it complements other analytical methods and helps visualize the structure of the activist population.

In your view, why is the combination of field research and digital methods essential? Do the limitations of online data manifest themselves, for example, in the representation of women?

I work with communities that are often referred to as “subaltern”—that is, groups affected by systemic exclusion with limited access to education or economic resources.

Online data tends to represent the more educated segment of the community—very often men. If I relied solely on this data, I would get a distorted picture of which issues resonate within these communities. This is precisely where the great importance of field research becomes apparent, as it allows me to verify to what extent the topics discussed online are truly important to the broader community as well.

This also applies to the issue of gender. Feminism and criticism of gender inequalities are among the key themes of anti-caste activism; yet women’s voices tend to be less visible in the online space. In many cases, women still face barriers to accessing education and the public sphere, which is also reflected in the structure of the data I work with.

I would therefore like to focus more in the future on the Savari platform, which publishes texts by women involved in anti-caste activism. It could offer an important counterbalance to the narrative shaped predominantly by male authors.

Field research not only provides a space for dialogue with the people the research concerns but also serves as a participatory platform where their voices can be heard and where they can actively influence how the research is organized. It often turns out that everyday problems such as access to water, land, education, or employment are more fundamental to people’s daily lives than the topics dominating online discussions. In the context of activism, this illustrates the stark differences between the activism of more educated urban populations and that of people who often face direct physical violence and discrimination in rural areas.

The question often arises as to whether it is even possible to measure religion using data. What is your view on this?

Religious studies scholars usually say that religion itself cannot be measured. What we study are people, their behavior and actions, and their consequences in the world.

We do not analyze religion as an abstract actor in the world, but rather observe how people formulate and apply religious concepts in practice, what they mean for their lives, and what function they serve. Digital methods allow us to track, over a long time span, for example, how human societies rely on religious practices and interpretations of the world, and how these strategies change in response to external changes (e.g., political changes, pandemics, economic crises, armed conflicts, or social processes such as urbanization or migration).

How do large language models influence your research?

Very significantly. When I first started my research, I worked with thematic modeling using LDA (Latent Dirichlet Allocation). With the advent of large language models, the possibilities have expanded dramatically.

Today, many researchers use AI as an assistant for both programming and designing analytical procedures. Tasks that used to take days can now be completed much more quickly.

At the same time, this raises questions about the transparency and reproducibility of the analysis. Personally, I tend to be more cautious about using more general-purpose LLMs because I need to have clear control over how the results were obtained. On the other hand, I know colleagues who use agent-based models to create very complex simulations that would previously have required the work of an entire team.

What are you currently working on?

I’m researching how the online output of anti-caste activists changes depending on the political and social context.

I’m interested in the relationship between activist discourse and structural threats or political opportunities—for example, responses to the erosion of democratic institutions or legislative measures affecting religious and ethnic minorities.

I combine social science approaches with methods from the digital humanities and am expanding my dataset to include data from new platforms and online news outlets. The goal is to better understand how activist groups respond to social changes and how they seek to mobilize the public to defend civil rights.

Lastly, how do you think the digital humanities are transforming the perception of the work of humanities scholars?

The digital humanities and computational social sciences are entering the public sphere, particularly with the rise of artificial intelligence. Although they have been part of the work of both academics and everyday users for decades, their current pace of development is so rapid that it is difficult to keep up with them.

The traditional image of a humanities scholar sitting in an archive has become more of a stereotypical prejudice. Alongside this, research today often involves working with extensive databases, large digital corpora, and computational methods.

The humanities are thus becoming significantly more technology-driven. Researchers are increasingly working with so-called mixed methods (qualitative coding and computational analysis), programming, analyzing large datasets, and striving to keep pace with technological developments. In my view, it is precisely this transformation that represents one of the greatest challenges and opportunities in contemporary research.

How to Study the Past by Computational Approaches? Join us at CEDRR!