• Cornell Jackson King’s College London,
• Matthew Hammond King’s College London

King’s College London

One of the techniques that have recently been bringing value to the humanities is social network analysis. Social networks are defined and measured as connections among people, organisations, political entities (states and nations) and/or other units. Social network analysis is a theoretical perspective and a set of techniques used to understand these relationships (Valente 2010, pg. 3).

The People of Medieval Scotland (PoMS) database holds data on all known people between 1093 and 1314 mentioned in over 8600 contemporary documents. This was funded by the Arts and Humanities Research Council in the United Kingdom. The current research is part of the Transformation of Gaelic Scotland project funded by the Leverhulme Trust. This exploratory research has the goal of understanding the role of social networks among the elite of medieval Scotland. It also has the goal of exploring the appropriateness of social network analysis techniques for this data set, and perhaps for other similar collections.

Below are the key findings so far using social network analysis:

• Historians knew that Duncan II Earl of Fife was important but were surprised at the central role he played in charter witnessing. He witnessed the 2nd highest number of charters and had the highest number of co-witnesses by far. It is not clear why he has such a central role.

• A visualisation of the network of all witnesses that witnessed more than 20 charters revealed a timeline of charters, geographical concentrations of witnesses and norm-sharing cliques.

• Social network analysis revealed the central role the royal courts played in the diffusion of Scottish regnal sicut clause innovations among grantors of Scottish charters.

References:

Valente, Thomas W. (2010) Social Networks and Health: Models, Methods and Applications. Oxford: Oxford University Press

• Pim van Bree LAB1100,
• Geert Kessels LAB1100

LAB1100

In this paper we will explore the process of mapping memory landscapes by use of the web-based data management, analysis and visualisation environment ‘nodegoat’ (http://nodegoat.net/). We aim to dynamically organise fuzzy data, gathered during multiple interview sessions, in multimodal networks. We will use events connected to the 1965 anti-communist violence in Semarang as a case study. The digital recording of these events are the result of a series of workshops within the pilot project ‘Memory Landscapes; Anti-Communist Violence in Semarang  1965’ of dr. Martijn Eickhoff (NIOD - Institute for War, Holocaust and Genocide Studies in Amsterdam) organised in cooperation with the Universitas Katolik Soegijapranata (UNIKA) in Semarang. During these workshops, students from UNIKA collected data on these events in nodegoat by combining oral history and anthropological site research. The data includes relations between people as well as locations connected to the events of 1965 (e.g. places of mob violence, temporary detention, interrogation, torture, murder and mass burial). LAB1100 has developed nodegoat, conceptualised the data model used during the workshop and supervised the data entry processes in the field.

The digitisation of individual and community memory in nodegoat discloses an alternative network of non-official places of memory. Using our object-oriented environment in the workshops, interviewers store information provided by the interviewees instantly, consistently and without limitation. Following Actor-Network Theory (Latour, 2005), people/events/artefacts are considered equal: objects. This allows us to analyse individual accounts and map contradictory or conflicting connections within the collective. This establishes a process of self-identification of all objects involved, including all controversies that arise. The network takes on a rhizomatic perspective as any object can be connected to any other object by reference, as source of a relation, and for the configuration of location and date. The nonhierarchical workflow allows for various methodological approaches in mapping the nodes of the 1965 memory landscape. Our paper will expand on key features and issues related to the process of recording individual and community memory by means of the web-based research environment nodegoat.

• M. H. Beals Sheffield Hallam University

Sheffield Hallam University

In the first half of the nineteenth century, the number of newspapers published in Britain grew exponentially and spread far beyond the large urban centres into market towns and centres throughout the nation. Although these provincial newspapers remained weekly or bi-weekly publications throughout the period, they still required a significant amount of reportage to fill their four to eight pages. This material was shamelessly, and often haphazardly, gleaned from international periodicals in the form of scissors-and-paste reprints. Through these half-hearted shortcuts, we can develop a significant understanding of newspaper networks before the rise of international telegraphy and the slow decline of the scissors-and-paste system.

Utilising highly detailed transcriptions of newspaper content from the wider Anglophone world, and considering omissions, additions and typesetting errors, we can trace key dissemination pathways of news content from its origin in various British towns and colonies, through its many reprints, abridgments, summaries and commentaries, to the pages of provincial press. By mapping the shape and directionality of these network connections, a greater understanding of news dissemination and editorial links can be achieved. These networks can then form the statistical basis of further qualitative studies into the spread of ideas or interpersonal connections. However, close reading such as this requires painstaking transcription and careful examination of individual articles — processes that severely limit the speed and scale at which these networks can be constructed.

The paper will demonstrate how, through careful reflections on implicit processes undertaken during traditional close reading, and the adaptation of digital tools developed for distance reading and edition tracking, the mapping of these news networks can be significantly automated and the quantitative influence of key hubs can be preliminarily determined.