Communication data between people is a rich source for insights into societies and organizations in areas ranging from research on history to investigations on fraudulent behaviour. These data are typically heterogeneous datasets where communication networks between people and the times and geographical locations they take place are important aspects. We argue that these features make the area of temporal communications a promising application case for Linked Data (LD)-based methods combined with temporal network analyses. The key result of this paper is to present a framework, tools, and systems for creating, publishing, and analyzing historical LD from a network science perspective. The focus is on network analysis of epistolary network data (metadata about letters), based on recent advances in analysis of temporal communication networks and the behavioural patterns commonly found in them. To test, evaluate, and demonstrate the usability of the framework, this paper shows how network analysis has been applied to (1) the Dutch CKCC corpus (of ca. 20,000 letters), (2) the pan-European correspSearch corpus (of ca. 135,000 letters) with promising results. The tools presented have also been re-used successfully in other related systems, such as LetterSampo Finland (1809–1917) of 1.2 million historical letters.
Leskinen et al. (Sat,) studied this question.
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