The structure of the Arts & Humanities Citation Index: A mapping on the basis of aggregated citations among 1,157 journals

Using the Arts & Humanities Citation Index (A&HCI) 2008, we apply mapping techniques previously developed for mapping journal structures in the Science and Social Science Citation Indices. Citation relations among the 110,718 records were aggregated at the level of 1,157 journals specific to the A&HCI, and the journal structures are questioned on whether a cognitive structure can be reconstructed and visualized. Both cosine-normalization (bottom up) and factor analysis (top down) suggest a division into approximately twelve subsets. The relations among these subsets are explored using various visualization techniques. However, we were not able to retrieve this structure using the ISI Subject Categories, including the 25 categories which are specific to the A&HCI. We discuss options for validation such as against the categories of the Humanities Indicators of the American Academy of Arts and Sciences, the panel structure of the European Reference Index for the Humanities (ERIH), and compare our results with the curriculum organization of the Humanities Section of the College of Letters and Sciences of UCLA as an example of institutional organization.

💡 Research Summary

The paper investigates whether the Arts & Humanities Citation Index (A&HCI) can be used to map the internal structure of the humanities by aggregating citations at the journal level. Using the 2008 A&HCI dataset, the authors extracted 110,718 records belonging to 1,157 core journals (which represent 96 % of the index’s output). Two complementary analytical routes were pursued.

First, a bottom‑up network approach based on cosine similarity was applied. The raw citation matrix was transformed into a cosine‑normalized similarity matrix, thereby controlling for differences in journal size and for the sparsity typical of humanities citation data. The resulting similarity network was visualized with several tools (Pajek, VOSviewer, Gephi). Community detection revealed roughly twelve coherent clusters. These clusters correspond loosely to traditional humanities disciplines (e.g., Classics, Art History, Philosophy, Musicology) but also contain cross‑disciplinary groupings such as Gender Studies, Cultural Studies, and emerging Digital Humanities/Media Studies.

Second, a top‑down statistical approach was conducted via factor analysis. After performing a principal component extraction and varimax rotation, the same citation matrix yielded a set of factors with eigenvalues greater than one. The factor solution converged on a similar twelve‑factor structure, confirming the robustness of the clusters identified by cosine normalization. Factor loadings highlighted the same disciplinary cores and, importantly, showed that many journals load on multiple factors, reflecting the interdisciplinary nature of much humanities scholarship.

The authors then compared the derived structure with the existing ISI Subject Categories (including the 25 categories unique to A&HCI). They found a substantial mismatch: ISI categories assign each journal to a single, often overly broad, label, which fails to capture the multidimensional citation relationships uncovered by their analysis. Consequently, the paper explores external validation sources.

The American Academy of Arts & Sciences’ Humanities Indicators project provides a survey‑based classification of humanities departments into eleven broad topics (e.g., English, History, Philosophy, Religion, Ethnic, Gender, and Cultural Studies). The European Reference Index for the Humanities (ERIH) organizes journals into fifteen expert panels (e.g., Archaeology, Art, Classical Studies, Gender Studies, etc.). Mapping the twelve clusters onto these schemes shows considerable overlap, yet also highlights areas where the bibliometric map identifies fields not explicitly recognized by ERIH (e.g., Digital Humanities) or where ERIH’s panels split what the citation data treat as a single cohesive community.

A further validation step involved comparing the clusters with the curriculum structure of the Humanities Section of UCLA’s College of Letters and Sciences. The authors matched each cluster to UCLA’s departmental and programmatic organization, finding that most clusters align with existing majors or interdisciplinary programs, reinforcing the practical relevance of the citation‑based map.

The paper discusses several limitations. A&HCI’s coverage is journal‑centric; books, book chapters, and other non‑journal outputs—estimated to constitute over 70 % of humanities scholarship—are largely absent. This omission biases the citation network toward fields that publish more frequently in journals (e.g., philosophy, art history) and underrepresents disciplines that rely heavily on monographs (e.g., literary studies). The authors note the forthcoming Book Citation Index and the potential of Google Books data as avenues for extending the mapping to a more comprehensive representation of humanities communication.

Methodologically, the study demonstrates the value of combining cosine normalization (which preserves the raw relational geometry) with factor analysis (which extracts latent dimensions) to uncover a stable, interpretable structure. The resulting twelve‑cluster solution offers a data‑driven taxonomy that can inform research evaluation, policy making, and institutional restructuring within the humanities.

In conclusion, the authors successfully reconstruct a cognitive map of the humanities from A&HCI citation data, revealing a nuanced, interdisciplinary landscape that diverges from traditional ISI subject classifications. Their work underscores the need for richer data sources (including books) and provides a replicable analytical framework for future bibliometric studies of the humanities.