Conference Agenda

Historical network research often relies on links formed through specific interactions among historical entities, such as family relationships, political alliances, or correspondence. While these approaches have proven insightful, this study highlights the potential of another one: co-occurrence networks of historical entities. Using biographical data from Wikidata, I construct co-occurrence networks based on the idea that two entities are connected if a significant number of individuals are linked to both. As examples, I construct three separate co-occurrence networks: ancient Roman administrative positions, 20th-century conflicts, and modern German political parties. Graphical representations of these networks are presented, and the centrality values of the nodes are calculated. The analysis of the Ancient Roman network shows that positions like "proconsul" and "magister equitum," despite having fewer members, exhibit high closeness and betweenness centrality, making them critical for connecting other influential roles. In the 20th-century conflicts network, major global events like the world wars emerge as central nodes, while the "Vietnam War" displays high betweenness centrality, acting as a bridge between earlier and later conflicts. The German political parties network reveals clear ideological and temporal partitions, highlighting divisions between left-oriented and right-oriented parties, with further separations between historical and contemporary groups. These examples demonstrate that historical co-occurrence networks can yield meaningful results. They simplify complex data into clear network structures and adapt flexibly to diverse contexts where direct interaction data is limited. These qualities show that co-occurrence networks can offer insights alongside other network approaches.

Existing scholarship has shed light on structural barriers women faced in gaining intellectual recognition in the development of early modern science. While traditional research has given us insights into singular cases, a more comprehensive understanding of women’s presence (or lack thereof) is still to be identified. This study explores the application of network analysis to uncover the often-overlooked contributions of women in early modern science.

We employ a combination of distant reading, close reading, and network analysis. We cross reference a dataset of over mentions from over 400 works on early modern natural philosophy with datasets of early modern female authors, to investigate their appearance in the literature. Through a feminist archival approach, the study integrates data from different archives to identify explicit mentions of women in scientific discourse, as well as implicit, such as by proxy of a male scientist. Using networks to analyse these references to women scientists, who are typically absent from historiographical narratives, allows us to investigate their presence as embedded within the broader field of natural philosophy. Findings highlight the appearance of explicit references to for instance Maria Agnesi, and Laura Bassi, as well as indirect presences, such as Maria Margaretha Kirch and Caroline Herschel.

In this presentation, we showcase how we can integrate approaches from digital humanities, network science, and feminist history to create an integrated, more nuanced understanding of the past. We offer an examination of how archiving practices such as reparative description and counter-archiving can challenge biases in historical data representation.

The history of consumer credit in Europe goes back several hundred years. Extensive evidence of widespread consumer credit networks exists for Florence in the fifteenth century, earlier than much economic historiography penetrates. Summary transcriptions of account books in the 1420s and 1430s document myriad credit relations between dozens (actually, hundreds) of companies and shops on the one hand and thousands of Florentine households on the other in two-mode network form. Specifically, there is copious qualitative and quantitative evidence of high-quality Florentine cloth being sold on account to Florentine households, a very substantial part of the market under-examined relative to Florentine merchants’ export of high-quality cloth abroad. Descriptive analysis shows that consumer credit ties are distributed unevenly: some companies did much more local business than others. At the same time, most companies dealt with households of relatively similar wealth levels, and they trafficked in both high- and medium-quality cloth; there was little market ‘segmentation’ by wealth or luxury level. Family and neighborhood homophily are only weak predictors of who does business with whom; they were at most the core of wider networks of consumer credit. What structure does exist beyond market imperatives may have arisen due to baked-in accidental patterns of the past, or it may be linked to patterns within and across networks of personal credit exchanges and networks of company-to-company relationships of financing, production, and distribution. Concerning the latter, I intend to use ERGM modeling to explore some of the complex cross-network connections within Florence’s multiple-network ecology.

This project seeks to characterize the disappearance of the Pacific Electric rail system in Los Angeles County between 1911 and 1961. This system was the largest light rail system in the United States, accounting for nearly 5% of all rail laid at one point. Existing work, primarily qualitative has pointed to a variety of top down pressures such as the rise of the automobile, highway construction and revenue related concerns in the demise of Pacific Electric. However, these have often neglected the spatial component of such networks, leaving a significant gap in understanding how these larger forces played out at a system level. Los Angeles is a unique case due to the unique urbanization and suburbanization patterns driven by such an expansive system. Utilizing spatial network analysis of network representations of the rail system in five year intervals, I draw on community detection algorithms as a way of measuring fragmentation. I demonstrate that the patterns of rail closure created a system that was more cohesive than random and closely resembled a modern transit system in structure, pointing to the preservation of several key arteries. I then combine these results with archival documents concerning public commissions hearings, newspaper articles and other urban planning documents while also pointing to two periods of rapid network shrinkage in the late 1930s and late 1940s. This project highlights the need to study historic rail transit systems utilizing network analysis to better understand spatial and urban patterns and the interaction of transit and social structures.

This study examines gender bias in the investigative practices of medieval inquisitors, focusing on Albert of Castellario’s 1335 trial of the Waldensians in Giaveno, Italy. Situating our analysis within sociological and criminological frameworks, we conceptualize inquisitorial trials as structured yet discretionary information-gathering processes shaped by the inquisitor's judgments about which leads to follow and which testimonies to prioritize. Employing social network analysis and survival methods, we evaluate whether Albert demonstrated gendered biases in his investigative decisions, particularly regarding the weight assigned to testimonies from men versus women. Our findings demonstrate that Albert systematically prioritized testimonies from male informants, even when similar levels of incriminating evidence were present for both genders. This bias highlights the significant role of societal gender norms in shaping inquisitorial practices, raising questions about the reliability and representativeness of historical records of heretical movements. Beyond showing Albert’s gendered biases, this study underscores the broader utility of our methodological framework for addressing related historical inquiries, including the political motivations behind the medieval inquisition.