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The digital transformation has affected literary studies in a variety of ways. First, by making more materials available and second, by opening new avenues of doing research. Many digital approaches to text analysis developed in computer science, computational linguistics, and natural language processing however have primarily been applied to large collections of texts and literary corpora. While these forms of “distant reading” have already produced novel insights and have helped to ask entirely new research questions, methods of distant reading are not the only way of using computers to better understand the works of a single author. My talk will showcase some computational close readings of the American writer Herman Melville and will illustrate that categories of closeness and distance are in fact scalable and not necessarily oppositional. With such a “scalable reading” (Weitin), I will argue that the humanities may find a stance of continuity within the monumental infrastructural change we call digitization. Bio Dr. Dennis Mischke ist wissenschaftlicher Koordinator und Leiter der Geschäftsstelle des »Ada Lovelace Center for Digital Humanities (ADA)« der FU Berlin. Seine Arbeitsgebiete sind Digitale Literaturwissenschaft, Critical Infrastructure Studies, Daten - und Digitalkulturen sowie Digitale Hochschuldidaktik. Dem Studium der Anglistik / Amerikanistik, Medienwissenschaft und Kognitionswissenschaft in Potsdam und Sydney folgte die Promotion im Fach Amerikanistik an der Ruhr-Universität Bochum. Nach verschiedenen Post-Doc Stationen in Deutschland, USA und Australien, war er zuletzt Gründungskoordinator des »Netzwerk für Digitale Geisteswissenschaften« an der Universität Potsdam.

In this poster, researchers from different projects present the integration of existingTEI-encoded corpora into a repository and analysis infrastructure, as well as the benefits of this integration. The focus is not on resource creation (corpus design or text encoding), but on infrastructure integration, dissemination and re-use of existing resources. The NFDI consortium Text+ seeks the integration of already existing resources, for example through the publication of corpora in repositories. We present the publication of the corpora of the European Literary Text Collection in the TextGrid Repository, discuss their characteristics and the advantages of this integration. The poster was accepted and presented at the DH2023 conference in Graz.

Das Poster ist ein Beitrag zur Konferenz "Comparing Landscapes: Approaches to Space and Affect in Literary Fiction", die am 20. und 21. April 2023 in Bielefeld stattgefunden hat. Es stellt die Grundzüge des CANSpiN-Projekts dar. DFG Schwerpunktprogramm SPP 2207 “Computational Literary Studies“ Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "Computational Approaches to Narrative Space in 19th and 20th Century Novels" (CANSpiN) Online: https://gepris.dfg.de/gepris/projekt/508056813 https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-Computational_Approaches_to_Narrative_Space https://www.canspin.uni-rostock.de

Dieser Vortrag wurde auf dem Treffen des DFG-Schwerpunktprogramms "Computational Literary Studies" (SPP 2207) am 20/21.2.2023 in Göttingen gehalten. DFG Schwerpunktprogramm SPP 2207 “Computational Literary Studies“ Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "Computational Approaches to Narrative Space in 19th and 20th Century Novels" (CANSpiN) Online: https://gepris.dfg.de/gepris/projekt/508056813 https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-Computational_Approaches_to_Narrative_Space https://www.canspin.uni-rostock.de

This report lists and describes a selection of Natural Language Processing (NLP) tools which are considered to form a Corpus-Enrichment and NLP toolchain for common CLS research tasks. The tools were selected to be: • safely positioned in their life cycle, i.e., state-of-the art, and mature as well as continuously maintained, or in development and promised as CLS Infra Deliverables by March 2025 • as multilingual as possible (beyond English and several major European languages) • as interoperable as possible with other tools and texts in other languages.

This project compares various methods of text similarity detection to see which method works best for finding broad thematic similarities between literary texts

The analysis of textual variants allows us to explore how a given literary text came into being. This involves the analysis of the author’s writing process and aesthetic inspirations but also analysing others who influenced the history of the text, for example as a translator or as a publisher. This further involves the inquiry into the historical and social circumstances under which the text was carried forward. These investigations are particularly relevant to the humanities not only because important contributions can be attributed to the respective person, but also because together they are the basis on which literary scholars then constitute the text: By comparison they can decide which textual variant is most adequate in the context of their specific research. The path digital editors take to approach this question is that they gather source material to identify traces of alterations and compile a document with a complex annotation structure that contains all available textual variants. Machine learning and computational humanities methods have the potential to contribute to this type of research in several ways, because they can (1) improve data availability with automated enrichment, (2) examine a broader collection through their ability to process textual sources at high speed, and (3) expand the existing catalog of methodology in literary studies. The major challenge is that methods in natural language processing as a sub-field of machine learning assume a simplified, linear textual basis, and thus are not able to compare different textual variants with each other. In Part 1, it will be addressed how linear textual variants can be extracted from complex document structures so that existing text processing methods can be applied. In Part 2, it will be investigated how the methodologies of the different disciplines of machine learning and literary studies can be connected, to ensure that the proposed method and the obtained findings present a useful contribution in the respective disciplines. Here, we focus on the notion of text representation and introduce the new Word2Vec with Structure Prediction method for generating text representations in the context of structured corpora and show how it benefits the digital humanities. Finally in Part 3, novel, robust natural language processing methods that are capable of comparing different textual variants are presented and applied in two different research contexts: In the analysis of a historical collection of letters from individuals who shaped intellectual Berlin around 1800 and in the study of the famous Schlegel-Tieck Shakespeare translation, with its translatorship origin still partly unexplained today. Overall, this work aims to illustrate how transdisciplinary research between literary studies and machine learning leads to new insights and thus benefits both fields., Die Analyse von Textvarianten ermöglicht es zu erkunden, wie ein vorliegender, literarischer Text entstanden ist. Dies umfasst die Analyse der künstlerischen Inspirationen, aber auch die konkreten Personen, die in ihrer Rolle, sei es bspw. Autor, Übersetzer oder Verleger, Einfluss auf die Textgeschichte hatten, bis hin zur Untersuchung der historisch-sozialen Umstände, unter denen der Text weitergegeben wurde. Diese Untersuchungen sind so relevant für die Geisteswissenschaften, weil sie gemeinsam Grundlage sind, auf der Literaturwissenschaftler dann einen adäquaten Text konstituieren. Der Ansatz der digitalen Editionswissenschaften ist es, dafür Quelldokumente sammeln, die Spuren von Textänderungen einer bestimmten Person bzw. eines bestimmten Kontexts enthalten und diese in einer komplexen Dokumentstruktur festzuhalten. Methoden des maschinellen Lernens und der computergestützten Geisteswissenschaft haben das Potenzial auf verschiedene Weise einen Beitrag bei dieser Art der Forschung zu leisten, da sie mit automatisierter Anreicherung die Datenverfügbarkeit verbessern können, sie durch ihre hohe Geschwindigkeit im Verarbeiten von Textquellen eine breitere Quellensammlung untersuchen können und weil sie den existierenden Methodenkatalog der Literaturwissenschaften erweitern. Die große Herausforderung besteht darin, dass existierende Textverarbeitungsmethoden (NLP Methoden) üblicherweise von einer vereinfachten, linearen Textgrundlage ausgehen, also nicht in der Lage sind, verschiedene Textvarianten (textual variants) miteinander zu vergleichen. In dieser Arbeit wird deshalb in einem ersten Schritt erarbeitet, wie aus diesen komplexen Dokumentstrukturen lineare Textvarianten extrahiert werden können, sodass bestehende Textverarbeitungsmethoden angewandt werden können (Teil 1). In einem zweiten Schritt wird erarbeitet, welche Scharnierstellen es gibt, die die Methodiken der stark unterschiedlichen Disziplinen des maschinellen Lernens und der Literaturwissenschaft verbinden, sodass sichergestellt ist, dass die entwickelten Methoden und die damit erzielten Erkenntnisse in der jeweiligen Disziplin auch verwendbar sind. Dabei wird der Fokus auf den Begriff der Textrepräsentation gelegt und die neue Methode Word2Vec with Structure zur Erzeugung von Textrepräsentation im Kontext von strukturierten Korpora vorgestellt und gezeigt, wie diese in den digitalen Geisteswissenschaften verwendet werden kann (Teil 2). Zuletzt werden neue, robuste NLP Methoden vorgestellt, die in der Lage sind, Textvarianten zu vergleichen und diese werden in zwei verschiedenen Forschungskontexten angewandt: Bei der Analyse einer historischen Briefsammlung von Personen, die das intellektuelle Berlin um 1800 geprägt haben und bei der Untersuchung der berühmten Schlegel-Tieckschen Shakespeareübersetzung, mit ihrer bis heute teils ungeklärten Übersetzungsurheberschaft (Teil 3). Insgesamt soll diese Arbeit verdeutlichen, wie eine transdisziplinäre Forschung zwischen Literaturwissenschaft und maschinellem Lernen produktiv neue Ergebnisse in beiden Feldern liefern kann.

The following thesis is a critical description of the U.S. Local Color Corpus (USLoCo). USLoCo is a dataset and research tool of my own making. It is composed of 730 short stories, novellas, and serialized novel chapters that were published between 1865 and 1920. Each text is categorized by author, title, author’s race, author’s gender, date of publication, and its setting assigned to three regional definitions: U.S. state setting, subregional setting, and ecoregional setting. All texts fit a specific definition of “local color fiction” described in chapter two. The purpose of this thesis is to prepare literary scholars to employ USLoCo in their research or teaching practices. It provides a history of the local color genre, a history of scholarly work on the subject, a concise breakdown of the dataset alongside metadata, and some suggested applications as well as notes on preservation. After reading this thesis, scholars and students should be able to employ USLoCo knowledgeably, conscientiously, and effectively.

Gegenstand dieser Arbeit ist die Charakterisierung von Schlüsselstellen ausgewählter literarischer Werke auf der Grundlage computergestützter literatur- und sprachwissenschaftlicher Methoden. Im Zentrum der Untersuchungen steht die Frage, inwiefern sich der Begriff der Schlüsselstelle über stilistische oder sprachliche Merkmale definieren lässt. Der Begriff wird in einen fachwissenschaftlichen Kontext eingeordnet, wobei der Fokus auf den Disziplinen Literaturwissenschaft sowie Computational Literary Studies liegt. Unter Zuhilfenahme quantifizierender Verfahren werden die zitierten und nicht zitieren Stellen zweier literarischer Werke hinsichtlich ausgewählter textueller Merkmale eingehender analysiert. Ergebnisse zur Länge und Verteilung von Stellen im Text, deren Sentiment und den darin enthaltenen Wortarten werden vorgestellt sowie methodenkritisch interpretiert. Des Weiteren wird ein erster Ansatz zur Visualisierung der Ergebnisse präsentiert. Der zugehörige Prototyp soll zur Reflexion über die Relation einzelner Textstellen zum gesamten Text anregen. In der Arbeit werden diverse Abzweigungen offengelegt, deren konsekutive Verfolgung umfangreiches Forschungspotenzial verspricht.

The purpose of this article is to explore the effect of the emotions expressed in fictional stories on the emotions experienced by their readers. We use around 450 books from 9 different genres and their corresponding reviews from Goodreads. We use sentiment analysis, calculating three different types of sentiment values: the average book sentiment, the average review sentiment and the emotion story arc of each book. We use three different methods, namely, a dictionary-based approach, a transformer-based approach, and a vector-space model approach. We then define the plot type of every book by clustering the emotion story arc using k-means with Dynamic time warping Barycenter Averaging (DBA) as the distance metric. We test our hypotheses using linear regression models (ANCOVA) to analyze the covariance between the sentiment values of books and reviews.

The present study proposes an experimental exploration of the Romanian novel written between 1920 and 1940 through the use of stylometry, a method of distant reading employed for the statistical analysis of style. Drawing from the most recent advances in the field of computational stylistics, we select a formal standpoint from which we seek to investigate the relation between the Romanian novelistic canon and minor, tertiary novels published in the same. In our test cases, we will attempt to establish some of the more promising aspects of stylometric analysis, as well as single out the experiments that yield no relevant result. Because of the relative novelty of the method, the purpose of our investigations is to offer a kind of pilot experiment that can illustrate the benefits of using computational methods on Romanian literary corpora.

Folien zur Präsentation am 30.05.2022, die im Rahmen der InFoDiTexT+ Vortragsreihe SoSe 2022 stattfand.

The aim of this poster is to provide an overview of the principal objectives of the newly started H2020 Computational Literary Studies (CLS) project- https://www.clsinfra.io. CLS is a infrastructure project works to develop and bring together resources of high-quality data, tools and knowledge to aid new approaches to studying literature in the digital age. Conducting computational literary studies has a number of challenges and opportunities from multilingual and bringing together distributing information. At present, the landscape of literary data is diverse and fragmented. Even though many resources are currently available in digital libraries, archives, repositories, websites or catalogues, a lack of standardisation hinders how they are constructed, accessed and the extent to which they are reusable (Ciotti 2014). CLS project aims to federate these resources, with the tools needed to interrogate them, and with a widened base of users, in the spirit of the FAIR and CARE principles (Wilkinson et al. 2016). The resulting improvements will benefit researchers by bridging gaps between greater- and lesser- resourced communities in computational literary studies and beyond, ultimately offering opportunities to create new research and insight into our shared and varied European cultural heritage. Rather than building entirely new resources for literary studies, the project is committed to exploiting and connecting the already-existing efforts and initiatives, in order to acknowledge and utilize the immense human labour that has already been undertaken. Therefore, the project builds on recently- compiled high-quality literary corpora, such as DraCor and ELTeC (Fischer et al. 2019, Burnard et al. 2021, Schöch et al. in press), integrates existing tools for text analysis, e.g. TXM, stylo, multilingual NLP pipelines (Heiden 2010, Eder et al. 2016), and takes advantage of deep integration with two other infrastructural projects, namely the CLARIN and DARIAH ERICs. Consequently, the project aims at building a coherent ecosystem to foster the technical and intellectual findability and accessibility of relevant data. The ecosystem consists of (1) resources, i.e. text collections for drama, poetry and prose in several languages, (2) tools, (3) methodological and theoretical considerations, (4) a network of CLS scholars based at different European institutions, (5) a system of short-term research stays for both early career researchers and seasoned scholars, (6) a repository for training materials, as well as (7) an efficient dissemination strategy. This is achieved through a collaboration between participating institutions: Institute of Polish Language at the Polish Academy of Sciences, Poland; University of Potsdam, Germany; Austrian Academy of Sciences, Austria; National University of Distance Education, Spain; École Normale Supérieure de Lyon, France; Humboldt University of Berlin, German; Charles University, Czech Republic; Digital Research Infrastructure for the Arts and Humanities, France; Ghent Centre for Digital Humanities, Ghent University, Belgium; Belgrade Centre for Digital Humanities, Serbia; Huygens Institute for the History of the Netherlands (Royal Netherlands Academy of Arts and Sciences), Netherlands; Trier Center for Digital Humanities, Trier University, Germany; Moore Institute, National University of Ireland Galway, Ireland; This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 101004984. References Ciotti, Fabio. 2014. „Digital literary and cultural studies: the state of the art and perspectives“.Between4/8, 1-17.https://doi.org/10.13125/2039-6597/1392. Borgman, Christine. 2010. Scholarship in the Digital Age : Information, Infrastructure, andthe Internet. Cambridge, Mass & London: MIT Press. See https://www.dariah.euandhttps://www.clarin.eu. Burnard, Lou, Christof Schöch, and Carolin Odebrecht. 2021. „In search of comity: TEI fordistant reading“.Journal of the Text Encoding Initiative. https://doi.org/10.4000/jtei.3500. Eder, M., Rybicki, J. and Kestemont, M. 2016. Stylometry with R: a package forcomputational text analysis.R Journal, 8(1): 107-21.https://journal.r-project.org/archive/2016/RJ-2016-007/index.html Fischer, Frank, Ingo Börner, Matthias Göbel, Andrea Hechtl, Christopher Kittel, P. Miling, andPeer Trilcke. 2019. „Programmable Corpora: Introducing DraCor, an Infrastructure for theResearch on European Drama“. InBook of Abstractsof the Digital Humanities Conference2019. Utrecht: ADHO. Heiden, Serge. 2010. The TXM Platform: Building Open-Source Textual Analysis SoftwareCompatible with the TEI Encoding Scheme. In24th PacificAsia Conference on Language,Information and Computation(pp. 10 p.). Sendai, Japon.Retrieved fromhttp://halshs.archivesouvertes.fr/docs/00/54/97/64/PDF/paclic24_sheiden.pdf Schöch, Christof, Tomaz Erjavec, Roxana Patras, and Diana Santos (in press). „Creatingthe European Literary Text Collection (ELTeC): Challenges and Perspectives”.ModernLanguages Open. Wilkinson, Mark D., Michel Dumontier, IJsbrand Jan Aalbersberg, Gabrielle Appleton, MylesAxton, Arie Baak, Niklas Blomberg. 2016. „The FAIR Guiding Principles for Scientific DataManagement and Stewardship“.Scientific Data 3(1).https://doi.org/10.1038/sdata.2016.18.

Die Computational Literary Studies (CLS) sind ein interdisziplinäres Forschungsfeld im Schnittpunkt von Literaturwissenschaft, Computerlinguistik und Informatik, in dem digitale Forschungsdaten eine zentrale Rolle spielen. Elf Forschungsprojekte aus den CLS sind derzeit in einem DFG-Schwerpunktprogramm organisiert. Um die Forschungsdatenmanagement-Bedarfslandschaft in den Projekten zu erfassen und zu bedienen, wurde ein mehrstufiges Verfahren mit Interviewgesprächen, Analyseschritten und Reviewphasen implementiert. In Leitfaden-gestützten Interviews beantworteten die Teilnehmer*innen insgesamt 47 Fragen. Im Zuge der ersten Auswertung wurde ein Antworteninventar erstellt und den Projekten nochmals zur Überarbeitung zur Verfügung gestellt. Es zeigte sich u.a. ein breites Spektrum an Forschungsdaten und eine zentrale Rolle von kollaborativ genutzten Modellen und Programmcodes. Um die identifizierten Bedarfe zu bedienen, wurde zur Bündelung der Datenpublikationen eine Zenodo-Community eingerichtet. Ferner haben die Partnerinstitutionen nun die Möglichkeit, über eine gemeinsame Gitlab-Instanz kollaborativ an Datenbeständen zu arbeiten. Nach der Implementierung dieser pragmatischen Lösungen liegt der weitere Fokus nun auf der Entwicklung einer gemeinsamen Archivierungsstrategie. Ein Beitrag zur 8. Tagung des Verbands "Digital Humanities im deutschsprachigen Raum" - DHd 2022 Kulturen des digitalen Gedächtnisses.

Das Korpus enthält Lyrikanthologien, deren Fokus auf zeitgenössischen Gedichten liegt. Es setzt sich aus zwei Teilkorpora zusammen: Anthologien aus der Zeit des Realismus: Avenarius 1882, Bern 1878, Kneschke 1865, Moltke 1882, Polko 1861, Prutz 1859 und Willatzen 1875; Anthologien aus der Zeit der Jahrhundertwende um 1900: Arent 1885, Benzmann 1904, Bethge 1905, Bierbaum 1893 und 1894, Bonsels 1905, Federmann 1908, Friedrich 1911, Gemmel 1898, Huch 1911, Jacobowski 1899, Renner 1899 und Tille 1896. Eine Beschreibung des Korpus finden Sie unter https://doi.org/10.5281/zenodo.6053973 DFG Schwerpunktprogramm SPP 2207 "Computational Literary Studies" Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "The Beginnings of Modern Poetry –Modeling Literary History with Text Similarities" Online: https://gepris.dfg.de/gepris/projekt/424212127 https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-Beginnings_of_Poetry

We have explored gaps in teaching of research skills for computational literary studies to inform the CLS INFRA project’s own approach to training schools and chart the territory to gain broader insight into current CLS teaching practices. To understand supply we have manually annotated a sample of European university courses in Digital Humanities and summer school workshops. To index demand we set up an online survey to ask the community to evaluate a set of predetermined ‘skills’ based on its perceived future prospects in the field and teaching (1-5 scale response, 118 participants). The survey also offered a chance to observe the demographic structure of the CLS community. The prevalence of early career respondents indicates a new generational wave within computational literary studies. Participant gender was balanced, although introduction of variables such as career stage, self-reported proficiency, and discipline demonstrated skewness. Researchers who work in the field of CLS also report more experience in computational methods, which suggests that these go hand in hand in current practice. Despite the gap in skills education being more general in nature, we identified areas of heightened interest. These are the skills that make up the backbone of computational research: from designing the study to text collection, to multivariate analysis and statistical modeling. Survey responses reiterated that the current gap in schooling is quantitative rather than qualitative. Moreover, there was a consensus among participants that the institutionalized training of a new generation of researchers is instrumental to disciplinary advancement of CLS.

C’est désormais en ligne que nous lisons un article, partageons un brouillon, retrouvons une citation, consultons un dictionnaire : la numérisation a bouleversé notre rapport aux textes. S’agissant de textes littéraires que nous nous proposons d'explorer, le recours aux nouvelles technologies a un impact considérable. Cet article propose un survol des études littéraires computationnelles, choisissant de les désigner par une métaphore d’appareillage afin de souligner et même de prôner leur intégration non exclusive, prolongeant dans un dialogue épistémologique une pratique plus traditionnelle de la lecture de près. À terme, il est raisonnable de supposer que les outils statistiques et computationnels continueront d’entrer dans la panoplie générale des sciences humaines, qu’il deviendra anodin pour un littéraire de lancer une campagne de collecte de données, un calcul statistique ou la modélisation d’une hypothèse. As we now get online to read an article, share a draft, locate a citation, or look up a word, digitisation has deeply changed how we access texts. When those are literary and we intend to explore them, the use of new technologies has a huge impact. This article offers a glimpse of computational literary studies, which the author chooses to refer to through a metaphor of mechanical enhancement, as she stresses and advocates for their non-exclusive integration, their continuation of and conversation with more traditional practices of close reading. Over time, one can reasonably expect statistical and computational tools to keep seeping into the general Humanities kit, and the idea of a literary scholar starting a data collection, computing a statistics or modelling a hypothesis to become trivial.

The purpose of the central project is to actively support all research projects in the priority programme, to foster exchange and collaboration and to organize common activities. One of the central project’s focuses is to support and consult all researchers in the programme in questions related to research data management (RDM). Here, the aim is to identify all the heterogeneous requirements of the individual projects and the potential synergies regarding the data and the methods used, to develop common strategies and best practices that may be of interest for the entire field of Computational Literary Studies. For that purpose, the central project is performing programme-wide surveys to thoroughly describe a “landscape of requirements” in the research field. Furthermore, technological and infrastructural developments are constantly monitored to inform the researchers about new possibilities or to offer innovative infrastructural components. The central project is organizing central events, networking opportunities inter-project communication; including general meetings, working groups, workshops and colloquia for PhD candidates. It is also responsible for the external communication of results and developments from within the programme into the wider community, and for including external researchers into the activities of the programme. Finally, the implementation of measures and policies to support early career researchers and to promote gender equality are integral parts of the central project’s responsibilities. DFG Schwerpunktprogramm SPP 2207 "Computational Literary Studies" Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "Zentralprojekt des SPP CLS" Online: https://gepris.dfg.de/gepris/projekt/424212012 https://dfg-spp-cls.github.io/about.html

Das Poster präsentiert ein Tagset zur Analyse und Annotation von Gattungen, Emotionen und Emotionsmarkern in lyrischen Texten. Mit dem Tagsetlassen sich zum Beispiel Fragen folgender Art untersuchen: Welche Emotionen werden in den annotierten Texten am häufigsten gestaltet? Welche Gattungen kommen am häufigsten vor? Gibt es Emotionen, die in bestimmten Gattungen über- und in anderen Gattungen unterrepräsentiert sind? Hängen manche Emotionen besonders eng mit bestimmten Typen von Emotionsmarkern zusammen? Das Tagset erlaubt in puncto Gattungen die Angabe einer oder mehrerer thematischer Gattungen (Naturlyrik, Liebeslyrik usw.) und nicht-thematischer Gattungen(Ballade, Sonett usw.) sowiedie Annotation der situativen Bestimmtheit. Für die Analyse der Emotionsgestaltung steht eine Liste von ca. 40 diskreten Emotionen zur Verfügung, wobei die Emotionsannotationenzusätzliche Angaben zum Beispiel zur zuschreibenden Instanz oder zur Trägerinstanz der Emotion enthalten können. Ergänzen lässt sich die Emotionsannotation durch die Angabe von vier verschiedenen Emotionsmarker-Typen, etwa Emotionswörtern oder mit Emotionen verknüpften Situationen. Das Tagset wird entwickelt und eingesetzt im Projekt „The Beginnings of Modern Poetry“ innerhalb des DFG-Schwerpunktprogramms „Computational Literary Studies“. DFG Schwerpunktprogramm SPP 2207 "Computational Literary Studies" Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "The Beginnings of Modern Poetry –Modeling Literary History with Text Similarities" Online: https://gepris.dfg.de/gepris/projekt/424212127 https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-Beginnings_of_Poetry

Das Poster pr��sentiert ein Tagset zur Analyse und Annotation von Gattungen, Emotionen und Emotionsmarkern in lyrischen Texten. Mit dem Tagset lassen sich zum Beispiel Fragen folgender Art untersuchen: Welche Emotionen werden in den annotierten Texten am h��ufigsten gestaltet? Welche Gattungen kommen am h��ufigsten vor? Gibt es Emotionen, die in bestimmten Gattungen ��ber- und in anderen Gattungen unterrepr��sentiert sind? H��ngen manche Emotionen besonders eng mit bestimmten Typen von Emotionsmarkern zusammen? Das Tagset erlaubt in puncto Gattungen die Angabe einer oder mehrerer thematischer Gattungen (Naturlyrik, Liebeslyrik usw.) und nicht-thematischer Gattungen (Ballade, Sonett usw.) sowie die Annotation der situativen Bestimmtheit. F��r die Analyse der Emotionsgestaltung steht eine Liste von ca. 40 diskreten Emotionen zur Verf��gung, wobei die Emotionsannotationen zus��tzliche Angaben zum Beispiel zur zuschreibenden Instanz oder zur Tr��gerinstanz der Emotion enthalten k��nnen. Erg��nzen l��sst sich die Emotionsannotation durch die Angabe von vier verschiedenen Emotionsmarker-Typen, etwa Emotionsw��rtern oder mit Emotionen verkn��pften Situationen. Das Tagset wird entwickelt und eingesetzt im Projekt ���The Beginnings of Modern Poetry��� innerhalb des DFG-Schwerpunktprogramms ���Computational Literary Studies���. DFG Schwerpunktprogramm SPP 2207 "Computational Literary Studies" Online: https://gepris.dfg.de/gepris/projekt/402743989 https://dfg-spp-cls.github.io/ Teilprojekt: "The Beginnings of Modern Poetry ��� Modeling Literary History with Text Similarities" Online: https://gepris.dfg.de/gepris/projekt/424212127 https://dfg-spp-cls.github.io/projects_en/2020/01/24/TP-Beginnings_of_Poetry

The "replication crisis" that has been raging in fields like Psychology (Open Science Collaboration 2015) or Medicine (Ioannidis 2005) for years has recently reached the field of Artificial Intelligence (Barber 2019). One of the key conferences in the field, NeurIPS, has reacted by appointing 'reproducibility chairs' in their organizing committee1. In the Digital Humanities, and particularly in Computational Literary Studies (CLS), there is an increasing awareness of the crucial role played by replication in evidence-based research. Relevant disciplinary developments include the increased importance of evaluation in text analysis and the increased interest in making research transparent through publicly accessible data and code (open source, open data). Specific impulses include Geoffrey Rockwell and Stéfan Sinclair's re-enactments of pre-digital studies (Sinclair and Rockwell 2015) or the recent replication study by Nan Z. Da (Da 2019). The paper has been met by an avalanche of responses that pushed back several of its key claims, including its rather sweeping condemnation of the replicated papers. However, an important point got buried in the process: that replication is indeed a valuable goal and practice.2 As stated in the Open Science Collaboration paper: "Replication can increase certainty when findings are reproduced and promote innovation when they are not" (Open Science Collaboration 2015, 943). As a consequence, the panel aims to raise a number of issues regarding the place, types, challenges and affordances, both on a practical and on a policy or community level, of replication in CLS. Several impulse papers will address key aspects of the issue: recent experience with attempts at replication of specific papers; policies dealing with replication in fields with more experience in the issue; conceptual and terminological clarification with regard to replication studies; and proposals for a way forward with replication as a community task or a policy issue. Bibliography Barber, Gregory. 2019. “Artificial Intelligence Confronts a ‘Reproducibility’ Crisis.” Wired, 2019. https://www.wired.com/story/artificial-intelligence-confronts-reproducibility-crisis/. Da, Nan Z. 2019. “The Computational Case Against Computational Literary Studies.” Critical Inquiry 45 (3): 601–39. https://www.journals.uchicago.edu/doi/abs/10.1086/702594. Ioannidis, J.A. 2005. “Contradicted and Initially Stronger Effects in Highly Cited Clinical Research.” JAMA, no. 294/2: 218–28. https://doi.org/https://doi:10.1001/jama.294.2.218. Open Science Collaboration. 2015. “Estimating the Reproducibility of Psychological Science.” Science, no. 349 (6251). https://science.sciencemag.org/content/349/6251/aac4716. Sinclair, Stéfan, and Geoffrey Rockwell. 2015. “Epistemologica.” 2015. https://github.com/sgsinclair/epistemologica. Notes 1. See: https://nips.cc/Conferences/2019/Committees. 2. For a selection of responses, see relevant contributions to Cultural Analytics.

This is a selected bibliography of computational literary studies, which was published in the Hungarian journal Helikon in 2020. Half of the selection contains Hungarian articles and books (1969–2019), the other half contains English, Italian and German articles and books from the last decade. Available formats: RIS, BiBTeX See also on Zotero Groups: https://www.zotero.org/groups/2490101/computational_literary_studies_helikon/ How to cite: Szilvia Maróthy, ed. „Válogatott bibliográfia [Selected Bibliography]”. In Szilvia Maróthy, ed. „Computational Literary Studies”. Special Issue, Helikon no. 1., 66 (2020). http://doi.org/10.5281/zenodo.3763817 Contributors: Dániel Golden, Margit Kiss, Károly Kokas, Andrea Parádi, Róbert Péter, Tiziano Tubay

This article examines the current state of research at the intersections of book history and digital humanities within the field of eighteenth-century studies. It addresses the popular and intellectual origins of the nexus between the book and the digital and surveys developments in this area of eighteenth-century studies in the last decade. The article examines current research trends within the field, with a particular focus on large-scale corpora and databases and the use of distant reading methods, and assesses what directions the future might hold for research in book history and digital humanities in the long eighteenth century. Not