{de} Im Forschungskolloquium werden internationale Projekte aus dem Bereich der digitalen Geisteswissenschaften vorgestellt. In diesem Semester wird ein Schwerpunkt auf Themen aus den digitalen Altertumswissenschaften liegen. Die Veranstaltung ist offen für externe Teilnehmer*innen, eine Registrierung ist nicht erforderlich, einfach diesen Link klicken: https://meet. in-berlin.de/dh_colloquium_fu_berlin Bei Rückfragen wenden Sie sich bitte an Prof. Dr. Stefan Heßbrüggen-Walter (s.hessbrueggen-walter@fu-berlin.de).
{en} This research colloquium presents international Digital Humanities projects. This semester will feature a number of talks from digital classics. The event is open to external participants, registration is not required, just click this link: https://meet. in-berlin.de/dh_colloquium_fu_berlin If you have any questions, please contact Prof. Dr. Stefan Heßbrüggen-Walter (s.hessbrueggen-walter@fu-berlin.de).
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Semesterplan / Schedule
Mi/Wed · 26.10.2022 · 18:15–19:45
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Maria Chiara Parisi (Universiteit van Amsterdam): »Mathematics & Scientific Explanation in Antiquity: A ›Slow Science‹ and ›Big Data‹ Study«
Science explainswhyreality is as it is. But what is scientific explanation? In philosophy of science, it is debated whether explanations are causal or can also be non-causal. Importantly, if all scientific explanations are causal, then mathematics does not explain, because mathematics provides non-causal, conceptual explanations. A virtually identical debate originated in antiquity with Proclus (412–485 CE), opposing two views:
- (1) mathematics is explanatory.
- (2) mathematics is not explanatory.
This ancient opposition ruled the debate on scientic explanation for millennia. An unsolved mystery surrounds (2), however. Proclus follows (1) and attributes (2) to Aristotle, contradicting Aristotle's own authoritativewritings.Whatdynamicsofthoughtcouldexplainsuchastarkandmomentous misattribution?
My main hypothesis is that, against current opinion, both the misattribution and the emergence of (2) are due to a conceptual shift regarding the objects of scientic knowledge. To show this, and to reconstruct this extremely consequential debate, I use a novel approach combining traditional, qualitative methods or ‘slow science’, and quantitative, computational techniques on a 'big data' corpus in Greek and Latin spanning 450 authors and nine centuries. This approach allows me to remain grounded in textual exegesis, while enlarging the evidence basis for a wide-scope investigation. In this talk, I focus on this novel approach. After introducing the theoretical framework, I discuss corpus selection and processing to enable (string and semantic) searches and collect relevant passages. Moreover, I illustrate the modelling of the concept of scientific explanation in Antiquity by adapting the Classical Model of Science (de Jong and Betti 2010) to the ancient context.
Mi/Wed · 15.02.2023 · 18:15–19:45
Rachele Sprugnoli (Università di Parma): »Sentiment Analysis for Latin: lexicons, annotation and automatic approaches«
The talk will present the development of sentiment lexicons for Latin, their publication as Linked Open Data in the context of the ERC project “LiLa: Linking Latin” and will report on the pilot manual annotation of sentiment in a set of poems written by Horace. Moreover, the results of a few preliminary experiments on the automatic detection of sentiment in Horace texts will be described.
Mi/Wed · 22.02.2023 · 18:15–19:45
Monica Berti (Universität Leipzig): »Canons of Ancient Historians in the Age of Linked Open Data«
The goal of this talk is to discuss characteristics of canons and catalogs of ancient literature in the digital age. The talk will present a project for extracting data about ancient Greek authors and works from still extant sources. The talk will show concrete examples about the extraction, annotation, and analysis of the language used by ancient authors to refer to other authors and works. The talk will address questions concerning the use of Linked Open Data best practices for collecting and sharing this data.
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(Die Veranstaltung im Vorlesungsverzeichnis.)
