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Dr Erik von Willebrand first described a family with bleeding symptoms in a Finnish publication in 1926. A closer look at this landmark publication sheds light on some pathophysiological aspects of von Willebrand disease that may be applicable even in the current era. We attempt to relay in this article how the teachings from this original description may provide a benchmark for further research in this condition. Non peer reviewed

This paper explores several approaches to assess temporal trends within archaeological and historical datasets containing records marked with significant extent of uncertainty accompanying their dating. We evaluate the strengths and pitfalls of these methodologies by employing two datasets: one comprising ancient shipwrecks and the other ancient Greek inscriptions. While these objects can, in principle, be precisely dated to specific years, they are often assigned broader date ranges, spanning centuries or longer historical periods. We propose that the most promising approaches involve using these date ranges as defining probabilities. By randomly assigning specific dates based on these probabilities, we enable hypothesis testing for temporal trends. As we want to encourage other scholars to employ the methods we propose, we offer a detailed description of the implementation of these methods using functions from the Python tempun package.

We evaluate four count-based and predictive distributional semantic models of Ancient Greek against AGREE, a composite benchmark of human judgements, to assess their ability to retrieve semantic relatedness. On the basis of the observations deriving from the analysis of the results, we design a procedure for a larger-scale intrinsic evaluation of count-based and predictive language models, including syntactic embeddings. We also propose possible ways of exploiting the different layers of the whole AGREE benchmark (including both human- and machine-generated data) and different evaluation metrics.

Citizen science is becoming a common tool to index historical records. We use cluster analysis on the engagement of participants in the 'Historical Database Suriname and Curaçao' citizen science project to build user profiles. These engagement patterns can be used to enhance and sustain participation of citizens.

In semantic typology, colexification refers to words with multiple meanings, either related (polysemy) or unrelated (homophony). Studies of cross-linguistic colexification have yielded insights into, e.g., psychology, historical linguistics and cognitive science (Xu et al., 2020; Brochhagen and Boleda, 2022; Schapper and Koptjevskaja-Tamm, 2022). While NLP research up until now has mainly focused on integrating syntactic typology (Naseem et al., 2012; Ponti et al., 2019; Chaudhary et al., 2019; Üstün et al., 2020; Ansell et al., 2021; Oncevay et al., 2022), we here investigate the potential of incorporating semantic typology, of which colexification is an example. We propose a framework for constructing a large-scale synset graph and learning language representations with node embedding algorithms. We demonstrate that cross-lingual colexification patterns provide a distinct signal for modelling language similarity and predicting typological features. Our representations achieve a 9.97% performance gain in predicting lexico-semantic typological features and expectantly contain a weaker syntactic signal. This study is the first attempt to learn language representations and model language similarities using semantic typology at a large scale, setting a new direction for multilingual NLP, especially for low-resource languages.

Social interaction is typically studied from the context of physical movement, where geographic distance and ease of connectivity influence the strength of interaction between regions. From the point of view of social media networks however, these limitations appear to still persist, despite interactions not being reliant on physical movement, suggesting non-physical geographic characteristics influence interaction between social communities. Unlike geotags, which provide explicit geographic information about social media users as coordinates, unstructured text presents an alternative perspective for the study of social interaction between regions, instead allowing for the comparison between the language used when mentioning locations in context. Our paper analyses the corpora associated with major cities across the UK, first vectorising Reddit comments through transformer-based embeddings, which capture semantic information, then using these to establish unsupervised clusters and similarity between them. We find that distinct groups emerge which broadly conform with established regional identities of locations across the UK, but with interesting deviations.

To date, there has been very little research on regional and rural music scenes in Germany. In this chapter, the case of Glitterhouse Records/Orange Blossom Special as important and rural actor of the German Independent/Underground Music Scene will be described and analyzed in terms of scene building and cultural memory. Started as a DIY Fanzine in 1981, the history of Glitterhouse Records as mailorder and record label began in 1984 in close relation to the North-American underground music of that time, e.g. as European partner of Sub Pop and Amphetamine Reptile Records. Founded and driven in Beverungen, a small town next to the river Weser in Eastern Westfalia and retaining a strong sense of its regional identity, the label gathered a strong meaning in the German scene and has not only outlasted many other urban-based labels, but gained even more importance through Orange Blossom Special, a festival that has taken place in the garden of the label’s premises since 1997. The festival constitutes a yearly crowd of about 2000-2500 people – most of them returning every year. Taking into account the socio-spatial setting of festivals, scenes and their connection to ‘the rural’, the analysis presented in this chapter focuses on the ability of Glitterhouse and OBS to build rural based memory as well as a community around music, linked to shared attitudes connected with the trans-local independent music scene. The chapter draws on interviews with the founders of Glitterhouse Records and OBS as well as festival attendees.

Stylometry is used to analyse the novels written by Bill and Hillary Clinton to see how much of their novels the political couple are actually writing.