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Innovative technologies are improving the accessibility, preservation, and searchability of born-digital and digitised records. In particular, Artificial Intelligence is opening new opportunities for archivists and researchers. However, the experience of scholars (particularly humanities scholars) and other users remain understudied. This article asks how and why researchers and general users are, or are not, using computational methods. This research is informed by an open-call survey, completed by 22 individuals, and semi-structured interviews with 33 professionals, including archivists, librarians, digital humanists, literary scholars, historians, and computer scientists. Drawing on these results, this article offers an analysis of user experiences of computational research methods applied to digitised and born-digital archives. With a focus on humanities and social science researchers, this article also discusses users who resist this kind of research, perhaps because they lack the skills necessary to engage with these materials at scale, or because they prefer to use more traditional methods, such as close reading and historical analysis. Here, we explore the uses of computational and more “traditional” research methodologies applied to digital records. We also make a series of recommendations to elevate users’ computational skills but also to improve the digital infrastructure to make archives more accessible and usable.
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Stored only when both papers are in the corpus — 15 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.