In this paper, we shed new light on the authenticity of the Corpus Caesarianum, a group of five commentaries describing the campaigns of Julius Caesar (100-44 BC), the founder of the Roman empire. While Caesar himself has authored at least part of these commentaries, the authorship of the rest of the texts remains a puzzle that has persisted for nineteen centuries. In particular, the role of Caesar's general Aulus Hirtius, who has claimed a role in shaping the corpus, has remained in contention. Determining the authorship of documents is an increasingly important authentication problem in information and computer science, with valuable applications, ranging from the domain of art history to counter-terrorism research.We describe two state-of-the-art authorship verification systems and benchmark them on 6 present-day evaluation corpora, as well as a Latin benchmark dataset. Regarding Caesar's writings, our analysis allow us to establish that Hirtius's claims to part of the corpus must be considered legitimate. We thus demonstrate how computational methods constitute a valuable methodological complement to traditional, expert-based approaches to document authentication.

This paper describes a co-creative text generation system applied within a science fiction setting to be used by an established novelist. The project was initiated as part of The Dutch Book Week, and the generated text will be published within a volume of science fiction stories. We explore the ramifications of applying Natural Language Generation within a cocreative process, and examine where the cocreative setting challenges both writer and machine. We employ a character-level language model to generate text based on a large corpus of Dutch novels that exposes a number of tunable parameters to the user. The system is used through a custom graphical user interface, that helps the writer to elicit, modify and incorporate suggestions by the text generation system. Besides a literary work, the output of the present project also includes user-generated meta-data that is expected to contribute to the quantitative evaluation of the text-generation system and the co-creative process involved.

Abstract

In this paper we report on an explorative study of the history of the twentieth century from a lexical point of view. As data, we use a diachronic collection of 270,000+ English-language articles harvested from the electronic archive of the well-known Time Magazine (1923Magazine ( -2006. We attempt to automatically identify significant shifts in the vocabulary used in this corpus using efficient, yet unsupervised computational methods, such as Parsimonious Language Models. We offer a qualitative interpretation of the outcome of our experiments in the light of momentous events in the twentieth century, such as the Second World War or the rise of the Internet. This paper follows up on a recent string of frequentist approaches to studying cultural history ('Culturomics'), in which the evolution of human culture is studied from a quantitative perspective, on the basis of lexical statistics extracted from large, textual data sets.