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The aim of this poster is to provide an overview of the work carried out in the CLS INFRA project and its conclusions for the field of Computational Literary Studies.

***ENGLISH BELOW*** Streszczenie Artykuł prezentuje analizę problematyki poruszanej na łamach „Tekstów Drugich” w latach 1990–2012 z wykorzystaniem metody modelowania tematycznego. Na podstawie 1923 artykułów z tego okresu autorzy uzyskali i poddali interpretacji 120 wyłonionych automatycznie słowozbiorów, tj. tematów obecnych na łamach pisma. Wyróżniono tematy stałe, a także takie, którymi zainteresowanie rosło lub malało. Zastosowanie metod ilościowych pozwoliło ująć historię dyscypliny nie tyle jako serię odrębnych etapów, ile ciągły proces, w ramach którego współistnieją różne konfiguracje zagadnień. ABSTRACT Topic modeling on „Second Texts” The paper analyses the thematic structure in the issues of the literary journal Second Texts, in the years 1990–2012, using the topic modelling methodology. On the basis of 1,923 articles from this period, the authors obtained and interpreted 120 automatically inferred topics from the subsequent issues of the journal. The analysis allowed for identification of permanent and seasonal topics, which appeared with growing or declining frequency overtime. The application of quantitative methods has made it possible to capture the history of the discipline not so much as a series of distinct phases, but rather as a continuous process built from different configurations of co-existing research interests. &nbsp

Computational Literary Studies Infrastructure, funded by the Horizon2020 grant scheme, is a four-year, pan-European project that aims to unify the diverse landscape of computational text analysis, in terms of available texts, tools, methods, practices and so forth, within its growing international user community. The project started out in February 2021, meaning that it has been underway for just over a year. In our poster we discuss the various deliverables and activities that have come out of the CLS INFRA project in its first quarter to give an idea of its impact in practice.

Computational Literary Studies Infrastructure, funded by the Horizon2020 grant scheme, is a four-year, pan-European project that aims to unify the diverse landscape of computational text analysis, in terms of available texts, tools, methods, practices and so forth, within its growing international user community. The project started out in February 2021, meaning that it has been underway for just over a year. In our poster we discuss the various deliverables and activities that have come out of the CLS INFRA project in its first quarter to give an idea of its impact in practice.&nbsp

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.

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

Computational Literary Studies Infrastructure, funded by the Horizon2020 grant scheme, is a four-year, pan-European project that aims to unify the diverse landscape of computational text analysis, in terms of available texts, tools, methods, practices and so forth, within its growing international user community. The project started out in February 2021, meaning that it has been underway for just over a year. In our poster we discuss the various deliverables and activities that have come out of the CLS INFRA project in its first quarter to give an idea of its impact in practice.

Project summary The digital age offers challenges and opportunities for completing research on Europe’s multilingual and interconnected literary heritage. Even though many resources are currently available in digital libraries, a lack of standardisation hinders their access and reuse. The EU funded CLS INFRA project will help build the shared and sustainable infrastructure needed to undertake literary studies in the digital age. The project will align these diverse resources with each other, with the tools needed to interrogate them, and with a widened base of users. The resulting improvements will benefit researchers by bridging gaps between greater and lesserresourced communities in computational literary studies and beyond, ultimately offering opportunities to create new research and insight into our shared and varied European cultural heritage. Executive summary This deliverable presents the first version of Data Management Plan for the Horizon 2020 project CLS INFRA. To maximise the potential of the present document as a living and functional project management tool, the team decided to accommodate to this present DMP all sorts of digital scholarly objects that qualify as data or software and that are deemed worthy to be captured and preserved for reuse. Following the Horizon 2020 Data Management Plan template and guidelines, the document first defines the scope and selection criteria for project outputs (1.1.) and provides a structured overview of data and software collected, created, and (re)used for and by the CLS INFRA project. The second, FAIR data chapter describes the provisions made or envisioned to accommodate the FAIR principles and thereby future usage of CLS INFRA data resources. The third chapter provides a similar FAIR assessment of software resources. The fourth chapter describes roles, responsibilities and practical commitments and safeguards that are in place for the successful implementation of the DMP. The fifth chapter covers data security aspects. In the final chapter, we accommodated discussions around ethical aspects such as safeguards for personal data handling and safeguards for adherence to intellectual property rights are discussed. While preparing the DMP, special attention has been given to domain and disciplinary specificities. The CLS INFRA Data Management Plan is a living document and shall be updated continuously throughout the project in line with the new information gathered via conducting the project activities

This online presentation aims to raise awareness about the ongoing COST Action “Distant Reading for European Literary History” (2017-2021). In the context of this networking project, “distant reading” is understood as an umbrella term for recent computational, and particularly quantitative, approaches to the study of large collections of texts. While the contribution of the Distant Reading paradigm to Literary Studies continues to be a matter of intense debate, we believe that recent quantitative approaches clearly provide an important methodological perspective that usefully complements, and at times challenges, more established approaches to literary history and theory in areas like authorship attribution, genre analysis, periodization, canonization and intertextuality. Fostering insight into cross-national, large- scale patterns and evolutions across European literary traditions thanks to its 26 participating countries, this COST Action aims to facilitate the creation of a broader, more inclusive and better- grounded account of European literary history and cultural identity. In terms of scientific objectives, the Action is currently coordinating the creation of a multilingual European Literary Text Collection (ELTeC) which will be used to establish best practices and develop innovative methods of Distant Reading for the multiple European literary traditions. Finally, we will use the experience of building ELTeC to investigate the theoretical consequences of Distant Reading approaches for literary history and literary theory, focusing in particular on the ways that the digital turn affects our understanding of the traditional literary definitions of the novel, the canon and literary periods.

The term 'distant reading' resonates across DH: It is played on in book titles (Distant Horizons, Underwood 2019) and adapted to new fields ('Distant Viewing', Arnold and Tilton 2019). It spurs alternative formulations ('Scalable Reading', Mueller 2012) and is present in mainstream media ("What is Distant Reading?", Schulz 2011). It is a popular and integrating term, but can take very specific meaning as well. However, the semantic content carried over in each case of adoption or adaption is often unclear. Recent debates, like the special issue of PMLA (On Franco Moretti’s Distant Reading 2017) or the paper by Nan Z. Da (Da 2019) and the reactions to it, have challenged some of the assumptions of 'distant reading'. Also, the polysemy of the term may have contributed to misunderstandings in these debates. Therefore, our aim is to recover the historicity of the term 'distant reading', first introduced by Franco Moretti (2000) in his discussion of world literature as a system, by delineating how its meaning has changed over time and reconstructing some of the key theoretical assumptions it carries both as a term, a concept and a practice. This contribution has emerged from work in the COST Action "Distant Reading for European Literary History" (CA16204, https://distant- reading.net), a pan-European, collaborative networking project launched in 2017.

The term 'distant reading' resonates across DH: It is played on in book titles (Distant Horizons, Underwood 2019) and adapted to new fields ('Distant Viewing', Arnold and Tilton 2019). It spurs alternative formulations ('Scalable Reading', Mueller 2012) and is present in mainstream media ("What is Distant Reading?", Schulz 2011). It is a popular and integrating term, but can take very specific meaning as well. However, the semantic content carried over in each case of adoption or adaption is often unclear. Recent debates, like the special issue of PMLA (On Franco Moretti’s Distant Reading 2017) or the paper by Nan Z. Da (Da 2019) and the reactions to it, have challenged some of the assumptions of 'distant reading'. Also, the polysemy of the term may have contributed to misunderstandings in these debates. Therefore, our aim is to recover the historicity of the term 'distant reading', first introduced by Franco Moretti (2000) in his discussion of world literature as a system, by delineating how its meaning has changed over time and reconstructing some of the key theoretical assumptions it carries both as a term, a concept and a practice. This contribution has emerged from work in the COST Action "Distant Reading for European Literary History" (CA16204, https://distant-reading.net), a pan-European, collaborative networking project launched in 2017.

Fictional prose can be broadly divided into narrative and discursive forms with direct speech being central to any discourse representation (alongside indirect reported speech and free indirect discourse). This distinction is crucial in digital literary studies and enables in - teresting forms of narratological or stylistic analysis. The difficulty of automatically detecting direct speech, however, is currently under-estimated. Rule-based systems that work reasonably well for modern languages struggle with (the lack of) typographical conventions in 19th-century literature. While machine learning approaches to sequence modeling can be applied to solve the task, they typically face a severed skewness in the availability of training material, especially for lesser resourced languages. In this paper, we report the result of a multilingual approach to direct speech detection in a diverse corpus of 19th-century fiction in 9 European languages. The proposed method fine-tunes a transformer architecture with multilingual sentence embedder on a minimal amount of annotated training in each language, and improves performance across languages with ambiguous direct speech marking, in comparison to a carefully constructed regular expression baseline.

This poster aims to stimulate awareness of the existence of the newly-established COST Action on “Distant Reading for European Literary History” (2017-2021). In the context of this networking project, “distant reading” is understood as an umbrella term for recent computational, and particularly quantitative, approaches to the study of large collections of texts. This paradigm is here applied to the multilingual literary traditions of Europe in the long nineteenth century.