Reception Reader: Exploring Text Reuse in Early Modern British Publications

• The authors are affiliated with the Department of Digital Humanities at the University of Helsinki in Helsinki, Finland.Source: RESEARCH PAPER · p. 1
• Reception Reader explores text reuse and reception studies through digital humanities and data visualisation, using EEBO-TCP and ECCO data.The listed keywords identify these areas and collections as the article's focus.Source: RESEARCH PAPER · p. 1
• The article is by Rosson, Mäkelä, Vaara, Mahadevan, Ryan, and Tolonen, and was published in 2023 in Journal of Open Humanities Data.The citation lists volume 9, article 5, pages 1–11.Source: RESEARCH PAPER · p. 1

• The Reception Reader1 lets users search EEBO-TCP2 and ECCO3, then explore temporally organised, document-section clusters of text reuse and switch between distant and close reading.The databases cover a considerable portion of books published in Britain between 1450 and 1800.Source: (1) INTRODUCTION · p. 2
• Digital humanities research has increasingly used systematic, data-driven approaches to study reception and intertextuality, following historically manual methods.Examples include de Bolla et al. (2020), Gavin (2016), and Ladd (2021).Source: (1) INTRODUCTION · p. 2
• Text reuse detection enables data-driven study of reception at scale, but shared text does not necessarily imply influence.Computational methods can cover many works and shared passages despite noisy data.Source: (1) INTRODUCTION · p. 2
• The tool is intended for humanities scholars and students, with a broader aim of widening access to computational research and promoting data literacy.It may also be used in project courses to introduce humanities students to data science and digital humanities.Source: (1) INTRODUCTION · p. 2

(2.1) METADATA SEARCH

• Metadata search accepts author names, title words, and combinations, supports prefix and fuzzy matching, and returns the top 100 results by match score.Results show document ID, publication year, author, and short title; columns are sortable with secondary sorting, and selecting a document ID opens the main interface.Source: (2.1) METADATA SEARCH · p. 2

(2.2) INTERACTIVE VISUALISATION

• The main interface pairs a beeswarm chart of reuse connections with a view of the reused text’s context; same-author documents are excluded from chart results.Outgoing connections are shown by default, while the “In” control switches to incoming connections and year filters restrict the displayed dots.Source: (2.2) INTERACTIVE VISUALISATION · pp. 2–3
• Chart positions encode publication year and the reused text’s location in the primary document, while dot colour indicates the time gap between publications.The force-directed Voronoi layout nudges dots to avoid overlap while clustering near their original positions; horizontal clusters, vertical bands, and widening cones can suggest different patterns of reuse over time.Source: (2.2) INTERACTIVE VISUALISATION · p. 3
• Hovering over a dot reveals connected-document metadata and the reused segment’s page, while clicking displays the segment’s context in the page viewer.When available, scanned pages for both documents show the reused text highlighted, enabling examination of its surrounding discourse and later-author commentary.Source: (2.2) INTERACTIVE VISUALISATION · pp. 3–4
• A sortable, searchable table offers an alternative view of connected documents, with each row corresponding to a chart dot and opening its reuse context when selected.The backend moved edge data from slow, unindexed Parquet queries on a local Spark cluster to MariaDB column-stores and indexed tables for online response times, with reused snippets omitted; a Node.js service retrieves edges, adds metadata, and returns results.Source: (2.2) INTERACTIVE VISUALISATION · p. 4, (2.3) TECHNICAL SETUP · pp. 4–5

(2.3) TECHNICAL SETUP

• For ECCO page display, the backend translates reuse-data character offsets to Octavo’s token-level page mappings, which provide page numbers and scanned-image coordinates for text highlights.The translation is needed because Octavo offsets include extra chapter-heading annotations; the frontend and backend are deployed as Docker images on Rahti.Source: (2.3) TECHNICAL SETUP · p. 5

(3.1) WHAT CAN FIRST-TIME USERS DO WITH THIS TOOL?

• Users can search familiar or interesting works, inspect reuse patterns in a chart, identify connected documents, open highlighted pages, and read around reused text.The workflow can then be repeated with another work, moving between distant and close reading.Source: (3.1) WHAT CAN FIRST-TIME USERS DO… · p. 5

(3.2) TYPES OF REUSE AND RESEARCH QUESTIONS

• Researchers can trace reuses of Shaftesbury’s A Letter Concerning Enthusiasm (1708) and investigate its connection and context with Astell’s An Enquiry After Wit (1722) (Figure 6).For detailed study, the tool links to Gale’s complete edition texts when the researcher’s institution has a licence.Source: (3.2) TYPES OF REUSE AND RESEARCH… · p. 5, Figure 6 · p. 6
• Textual overlaps range from quotations and reprints to publication artefacts, so identifying and analysing relevant instances depends on the research question.Source: (3.2) TYPES OF REUSE AND RESEARCH… · p. 5

TYPE OF REUSE EXAMPLES

• Examples of reuse include Latin, biblical, and famous quotations; longer passages from essays or treatises; and modified reuse of a specific work.Source: TYPE OF REUSE EXAMPLES · p. 6, Table 1 · p. 6
• Other examples include poetry reprinted in unexpected locations, hidden or obscured reuse, and possible artefacts such as publisher imprints or advertisements.Source: TYPE OF REUSE EXAMPLES · p. 6, Table 1 · p. 6
• The tool identifies frequently reused parts of an edition and supports study of full, partial, modified, and quoted reprints.It can help investigate both texts incorporated into an author’s work and an author’s work reused by others.Source: TYPE OF REUSE EXAMPLES · p. 6, Table 1 · p. 6
• The Reception Reader was used to trace reuse of David Hume’s Essays across the eighteenth century (Spencer & Tolonen, in press).The study supplemented the tool with chapter-heading information to segment the Essays into constituent parts.Source: TYPE OF REUSE EXAMPLES · p. 6
• Analysis of Bernard Mandeville’s works found consistent reuse from authors including Pierre Bayle, except in Modest Defence of Publick Stews, supporting an authorship puzzle.The exception suggested the work may have been written by another author, a theory advanced by other scholars; the tool can speed exploration of such literary puzzles.Source: TYPE OF REUSE EXAMPLES · p. 6

(4.1) DATA

• The book corpora required cluster computing and a minor reduction in detection quality, producing 961 million data points but also fragmented sequences and many duplicate links.The pairwise method does not account for reuse direction over time; accuracy evaluation is beyond this article’s focus.Source: (4.1) DATA · p. 7
• The BLAST-based method found all Treatise of Human Nature reuse instances included in EHU except footnotes; experts confirmed approximately 1,200 of 1,400 manually checked cases.The remaining cases were various repetitions.Source: (4.1) DATA · p. 7

(4.2) DATA SAMPLE: SHAKESPEARE

• The released Shakespeare-related EEBO-TCP and ECCO sample contains uncurated reuse fragments and metadata, excludes surrounding ECCO OCR text and images, and can be explored through the Reception Reader.It is free to use for research with citation and requires further filtering and processing for analysis.Source: (4.2) DATA SAMPLE: SHAKESPEARE · p. 7

(4.3) THE GREAT CHAIN OF DIGITAL TOOLS

• The Reception Reader builds on years of collaboration between humanities research and data science, illustrating the need to sustain research-oriented groups and connected digital humanities infrastructure.The tool follows earlier Octavo prototypes and static visualizations, and the paper frames it as one step in an ongoing progression of tools.Source: (4.3) THE GREAT CHAIN OF DIGITAL TOOLS · p. 8

(4.4) FUTURE DEVELOPMENT

• A Spark clustering pipeline reduced 1.9 billion two-way edges to 373 million defragmented passages and 49 million first-source clusters to address OCR fragmentation and intermediary links.The team plans to assess whether the consolidated dataset clarifies reuse patterns.Source: (4.4) FUTURE DEVELOPMENT · p. 8
• Planned navigation, filtering, bookmarking, sequential document browsing, and destination-page previews aim to help users focus on reuse instances relevant to their research needs.The team seeks user feedback to inform subsequent development.Source: (4.4) FUTURE DEVELOPMENT · p. 8
• The beeswarm chart’s density and clustering suggest reuse volume and trends, but publisher imprints, advertisements, and documents commenting on multiple sections can skew that visual impression.Planned work includes defragmenting adjacent instances, addressing confounding artefacts, and refining the chart.Source: (4.4) FUTURE DEVELOPMENT · pp. 8–9
• Future work could use reuse links to trace changes across editions and at section or chapter scale, extend the tool to other digitized datasets, and detect paraphrase-based semantic similarity.The architecture is extendable to openly available research materials, while semantic similarity is being explored with the TurkuNLP group.Source: (4.4) FUTURE DEVELOPMENT · p. 9

(5) CONCLUSION

• The Reception Reader is designed around specific research needs, with the aim of making research tasks easier for real users.The authors propose starting with those users and then considering who else could benefit from the tool.Source: (5) CONCLUSION · p. 9
• The tool uses text-reuse data for a targeted purpose, while that data also has potential applications in other areas.Source: (5) CONCLUSION · p. 9
• Developed partly through DARIAH-FI,5, the Reception Reader tests scaling researcher-built software from internal use to a wider audience working on similar topics.The authors envision those researchers exploring the data and discovering insights to add to their work.Source: (5) CONCLUSION · p. 9

• The Reception Reader is an HPC-HD software demo planned for evaluation in early 2023, with Gale data-access terms still to be negotiated because use cases rely on ECCO source data such as document images.Source: DATA ACCESSIBILITY STATEMENT · p. 9

• The Academy of Finland funded the HPC-HD project under Grants 1333716 and 1347706.Source: FUNDING INFORMATION · p. 10