Alberto Baccini

GN
3papers
2citations
Novelty32%
AI Score38

3 Papers

GNApr 27
Exploring the Shape of Economics: A Multilayer Network Analysis of Social Communities and Intellectual Similarity Among Journals Before and After the 2008 Financial Crisis

Alberto Baccini, Lucio Barabesi, Carlo Debernardi

This paper develops a multilayer network approach for exploring the evolution of scientific disciplines, using the case of economics before and after the 2008 global financial crisis as a large-scale empirical testing ground. The units of analysis are journals, linked by social and intellectual relationships. The analysis covers all journals indexed in EconLit across three years (2006, 2012 and 2019). In the most recent year (2019), the dataset includes 909 journals, over 30,000 editorial board members, more than 260,000 authors, 134,000 articles, and nearly 2 million cited references. For each period, we model journals as connected in a four-layer multiplex network: the social relationships are based on shared editors (interlocking editorship) and shared authors (interlocking authorship), while the intellectual ones are based on shared references (bibliographic coupling) and textual similarity between articles. These four layers are integrated using Similarity Network Fusion to produce unified similarity networks from which journal communities are identified. Comparing the field across the three periods reveals a high degree of structural continuity. Although research topics changed after the crisis, the fundamental social and intellectual relationships among journals remained remarkably stable. A major result of the analysis is that editorial networks play the dominant role in shaping hierarchies and legitimize knowledge production within the discipline. Whether this finding holds in other scientific disciplines remains an open question for future research.

GNApr 20
Self-referentiality and asymmetric knowledge flows between journals. The case of economics

Alberto Baccini, Carlo Debernardi

This paper investigates the evolution of self-referentiality and knowledge flows in economics journals before and after the 2008 financial crisis. Using a multi-level approach, we analyze patterns at the discipline, cluster, and journal levels, combining citational measures with a classification of journals based on intellectual similarity and social proximity. At the aggregate level, results suggest a general decline in self-referentiality, indicating increased openness across the discipline. However, this trend conceals substantial heterogeneity. At finer levels of analysis, two clusters - CORE and Finance - emerge as persistent outliers, exhibiting very high levels of self-referentiality. While Finance experienced a gradual reduction over time, the CORE shows increasing closure. By examining reference asymmetries, we uncover a hierarchical structure of knowledge flows. The CORE operates as a central hub and net exporter of knowledge to all other clusters, particularly to the traditional core fields of economics, whereas Finance acts as a net exporter only within its own domain and remains dependent on the CORE. These asymmetries are reinforced at the level of individual journals, where a small set of top journals occupies the apex of a hierarchically ordered system of knowledge transmission. We argue that these patterns reflect the interplay between intellectual dynamics and organizational structures, particularly the role of editorial networks in shaping access to publication and visibility. The findings suggest that, following the financial crisis, economics has experienced a process of increasing epistemic and organizational closure at its core, alongside greater openness in peripheral areas. This dual dynamic raises questions about the representativeness of top journals and the evolving structure of the discipline.

DLMar 23
A Stock-Flow Framework for Editorial Board Dynamics: The Case of Economics Journals, 1866-2019

Alberto Baccini

Research on the editorial boards of scholarly journals has predominantly relied on static, cross-sectional data, focusing on their composition or interlocking editorships at single points in time. To address this gap, a formal stock-flow framework is developed for analyzing the longitudinal dynamics of editorial boards. The model integrates three interconnected layers: journal demographics, the dynamics of editorial positions, and the dynamics of board members. This framework is applied to the Gatekeepers of Economics Longitudinal Database (GOELD), which contains annual snapshots of editorial boards for approximately 1,700 economics journals from 1866 to 2006 (by decade), plus the years 2012 and 2019. The period until 1946 was characterized by small-scale: few journals and compact editorial communities. The decade from 1946 to 1956 marked the shift toward a ''big science'' model, initiating an era of expansionary growth fueled primarily by the founding of new journals. The contemporary period (2006-2019) appears to represent a structural break, characterized by low flux and more stable and more closed editorial communities. The results shows that the proposed framework enables a dynamic, long-term analysis of how journals and their gatekeeping systems evolve, grow, and structure themselves.