Luc Boltanski, in his book Investigations and Conspiracies, explores the modern detective novel as an expression of political imagination. The author posits that this genre was a specific product of the 19th-century nation-state. Detectives and investigators acted as guardians and monitors of the nation-state’s function of ensuring and upholding justice, whose stability was threatened by external and internal enemies.

The English and French states developed different methods of exercising power, which were reflected in their criminal novels. In England, detectives—such as the most famous, Sherlock Holmes—operated primarily within the social sphere of the elite. The English state was built on a compromise between the Crown and Parliament, so secrets and crimes had the potential to weaken this class's power. In the French context, represented by Commissioner Maigret, the source of order lay in the administration, which unified classes into the singular organism of the Republic.

My interest lies in the Second Polish Republic—a state that existed from 1918 to 1939. The history of this short-lived political entity was tumultuous and encompassed two developmental visions. Since the Second Polish Republic was a relatively new state with an unestablished administrative structure, the paths of interaction for the main characters could resemble both the contexts depicted in English and French novels. Investigators might remain within their own class (elites) or traverse various social environments.

I analyze a corpus of criminal novels from the Crime Stories of Pre-War Warsaw series to reconstruct the map of relationships detectives and investigators engage in. For the analysis, I employ the extraction of interpersonal relationships within the texts. This involves the automatic detection of individuals mentioned in the text and the verb expressions connecting them (at the sentence level). The next step is to reconstruct the network in each novel, where each character is a node, and direct interactions between two or more characters serve as edges (e.g., "Krzysztof took Hanna for a car ride, Szalski listened to their conversation from the back seat"). This approach goes beyond the previously used conversational network extractions (Elson et al., 2010) to reconstruct a map of all social relationships between characters in the novels (Lee & Yeung, 2012).

Subsequently, the ego-network of the main character is analyzed, encoding the class positions of surrounding characters and the investigator himself. This analysis infers measures of the character’s social embeddedness within the environment surrounding him and his investigation. The study will reveal whether the social trajectories of Polish investigators resemble the republican (multi-class/mosaic) consciousness of Maigret, the elitist approach of Holmes, or present a unique quality specific to the ephemeral political organism that was the Second Polish Republic.

Inquisitions were established by the Catholic Church in the 13th century to systematically investigate and suppress religious dissent through formal trial procedures. These trials were led by papally appointed inquisitors and documented by notaries, working to gather incriminating evidence against individuals through testimonies. Extant inquisition registers allow us to extract historical incrimination networks, but also raise methodological questions about their optimal representation and analysis. Given the virtual irrevocability of incriminations, we can conceptualize them as quasi-states and use Exponential Random Graph Models (ERGMs) to study the long-term aggregated characteristics of incriminations. However, the ERGM model needs to be adapted to account for the inquisitors' practice of summoning individuals. We can conceptualize incriminations as dyadic events and apply Dynamic Network Actor Models (DyNAM) to focus on individual decision-making patterns. However, as one deponent could incriminate multiple others, Relational Hyperevent Models (RHEM) might be more appropriate as they account for the polyadic nature of incriminations. In this talk, we compare these three approaches by applying them to incrimination networks collected from multiple medieval inquisition registers.

Historians are pre-occupied with telling ‘what happened’. Even so, how they do so in a digital context is confounded by a simple dilemma: how can history itself – not just its lists of places, people, or artifacts - be represented as structured data? Historical scholars are avid users of computation, but there remains no sure model for considering history-as-data. Conversely, existing models for structured data for events or actions are not only not historiographically robust, most reify historical events - something antithetical to modern historical theories and philosophical premises around what constitutes history itself. Networks provide a solution, but their use requires a clear approach to types of nodes and a vocabulary of edges.

Nanohistory.org is an open-source prototype platform designed to test drive the degree to which history itself can be represented as structured data using network and graph theory as the interface between computation and historical theories.

This paper will outline its theoretical foundations to illustrate how creation of the smallest historical forms possible, the nanohistory (a statement of historical action cast as a named directed graph), allows for the documentation and analysis of more complex historical phenomena that is historiographically robust, and well-structured data. Nanohistory.org functions as a digital annal, capturing provenance, agency, and multi-vocality in a way that is both machine and human readable. Rendering historical knowledge as a discursive narrative network positions history-as-data between the lists and datasets of historical evidence, and the prose of historical scholarship. The result is transformation of historical discourse into a multi-dimensional ergodic k-partite network, complete with histories’ multi-faceted pathways, mapping conflict, colligation, and confluence across a variety of historical records.

This paper examines the Dutch Cape Colony. Serial sources make it possible to reconstruct social networks that provide insight into the initial social conditions of this settlement. Baptism registers, in particular, are highly suitable for this purpose, as they document the majority of the Christian population. By combining these data with lists of colonial officials, it becomes possible to assess the extent to which colonial authorities were open to interaction with the broader population. The Cape Colony was originally established as a refreshment station, and in the early years of settlement, there were no particularly attractive factor endowments, such as cash crops or minerals. According to new institutional economists, this would suggest that the Cape Colony was more likely to develop open-access institutions. However, access to power in the early modern period should not be equated with participation in the political system. Genuine democracy had not yet emerged, which is why it is more appropriate to speak of access rather than participation. To better understand this, it is essential to study the networks of those in power. Network research can reveal the extent to which the political elite remained closed off or engaged with the broader population. Scholars such as Putnam have previously argued that broad, open networks can be considered a form of social capital that contributes to a well-functioning society and political system.

The Reform War (1858-1860) was one of the most violent and politically polarized conflicts of 19th-century Mexico. The Liberal victory led to an official historical narrative that oversimplified the war, obscuring the complexities of wartime society. To challenge this simplification, we analyze personal diaries as firsthand accounts that reveal the structure and dynamics of wartime social networks. In previous research, we reconstructed the social network of Juan de Vildósola’s Diary using natural language processing (NLP), text mining, and network science. The resulting network, modeled as a subgraph of a larger system with a Barabási-Albert structure, uncovered key actors, affiliations, and interactions within his social sphere. Expanding this approach, we analyze four additional diaries from the same period, written by individuals with diverse political affiliations. Using NLP, we extract and normalize entity mentions to reconstruct social networks, comparing structural patterns across different perspectives. This study validates previous findings while offering new insights into how personal experiences shaped social relations during the war. Our research highlights the potential of network analysis for reinterpreting historical processes, addressing key challenges in historical network research such as data incompleteness, ambiguity, and bias in personal accounts. By demonstrating how personal diaries serve as valuable datasets for social network reconstruction, we provide a methodological foundation for further studies on civil conflicts through computational and relational approaches.