Visualizing the Transcribe Bentham Corpus
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The document outlines the UCL Bentham Project and its Transcribe Bentham initiative, which aims to create a scholarly edition of the works of jurist and philosopher Jeremy Bentham by transcribing historical manuscripts. It discusses various methods for visualizing the transcribed corpus, including lexical extraction and co-occurrence networks, alongside the project's progress and the challenges faced. Additionally, it highlights tools and techniques used for lexical analyses and the engagement of a crowdsourcing community in transcribing material.
![Other Lexical Analyses
• TXM “textometry” tool
– Automatic part-of-
speech tagging
– Partition texts according
to metadata
– Query corpus using
linguistic criteria
– Statistical analyses
(overrepresentation,
underrepresentation)
72
[ http://textometrie.ens-lyon.fr/?lang=en ]](https://image.slidesharecdn.com/ucldhpresruiz-161216160828/85/Visualizing-the-Transcribe-Bentham-Corpus-72-320.jpg)
Visualizing the Transcribe Bentham Corpus
- 1. Visualizing the Transcribe Bentham Corpus Frédérique Mélanie, Estelle Tieberghien, Pablo Ruiz Fabo, Thierry Poibeau LATTICE Lab: ENS – CNRS – U Paris 3, PSL – USPC Tim Causer, Melissa Terras UCL Bentham Project, UCL Digital Humanities UCLDH Seminar, December 2016
- 2. Outline • UCL Bentham Project & Transcribe Bentham • How navigate this corpus? Visualizations – Lexical extraction – Co-occurrence networks • Static view and Temporal evolution • Evaluation and Challenges • Other corpus explorations via visualization • Distant Reading Module, WordTree • Other lexical analyses 2
- 3. Jeremy Bentham (1748-1832) •Jurist, philosopher, and legal and social reformer •Leading theorist in Anglo-American philosophy of law •Influenced the development of welfarism •Advocated utilitarianism •Animal rights, •Work on the “panopticon” •Not founder of UCL, but... •60,000 folios in UCL Sp. Collections •40,000 untranscribed •Auto-icon
- 4. The Bentham Project • http://www.ucl.ac.uk/Bentham-Project/ • Since 1959 • “aims to produce a new scholarly edition of the works and correspondence of Jeremy Bentham” • twenty six volumes of the new Collected Works have been published • 50 years to transcribe 20,000 folios • Previous AHRC grant catalogued the manuscripts – http://www.benthampapers.ucl.ac.uk/
- 10. Facts and Figures (as of 1st July 2016) • 16,205 manuscripts transcribed/partially-transcribed • 15,351 (94%) checked and approved • 83,955 visits • 34,359 unique views • Average session time: 14 minutes 13 seconds • 140 countries • 514 people have transcribed something • Most of the work done by the 26 Super Transcribers • Average of 54 transcripts edited since the start of the project • Average of 56 per week during the last twelve months • Greatest number of transcripts in any one week: 300 (w/c 14 June • 2014)
- 11. Transcribe Bentham progress, 8 September 2010 to 20 March 2015 0 2000 4000 6000 8000 10000 12000 8 Sep 2010 5 Nov 2011 30 Dec 2010 25 Feb 2011 15 Apr 2011 17 Jun 2011 12 Aug 2011 7 Oct 2011 2 Dec 2011 27 Jan 2012 23 Mar 2012 18 May 2012 13 Jul 2012 7 Sep 2012 2 Nov 2012 28 Dec 2012 22 Feb 2013 26 Apr 2013 21 Jun 2013 16 Aug 2013 11 Oct 2013 6 Dec 2013 31 Jan 2014 28 Mar 2014 23 May 2014 18 Jul 2014 12 Sep 2014 7 Nov 2014 9 Jan 2015 6 Mar 2015 Manuscripts worked on Completed transcripts NYT article BL manuscripts made available
- 12. With thanks to: •Prof Philip Schofield (UCL Bentham Project, Principal Investigator) •Dr Tim Causer (Bentham Project) •Dr Kris Grint (Bentham Project) •Richard Davis (University of London Computer Centre •José Martin (ULCC) •Martin Moyle (UCL Library Services) •Lesley Pitman (UCL Library Services) •Tony Slade (UCL Creative Media) •Miguel Faleiro Rodrigues, Alejandro Salinas Lopez, and Raheel Nabi (UCL Creative Media) •Dr Arnold Hunt (British Library) •Anna-Maria Sichani (Bentham Project) •Dr Justin Tonra (National University of Ireland Galway) and Dr Valerie Wallace (Victoria University Wellington), bother formerly of the Bentham Project •All the partners in Transcriptorium http://transcriptorium.eu/consortium/ •And Transcribe Bentham’s volunteers! •Project previously funded by the AHRC and the Andrew W. Mellon Foundation
- 13. Outline • UCL Bentham Project & Transcribe Bentham • How navigate this corpus? Visualizations – Lexical extraction – Co-occurrence networks • Static view and Temporal evolution • Evaluation and Challenges • Other corpus explorations via visualization • Distant Reading Module, WordTree • Other lexical analyses 13
- 14. Relevant access to a large corpus 14
- 15. Relevant access to a large corpus • A search index? • Topic models? • Corpus cartography? Challenges for this corpus • Not an all-English corpus • Difficulties posed by an historical variety • Technical language • Revision history, additions and deletions 15
- 16. Stats for analyzed corpus sample • Total TEI files: 29,900 • In English: 29,400 • That we dated: 16,700 • We only visualized English transcripts that we could date (with a simple heuristic)1 • Work is based on ca. 55% of the all the TEI files in our sample 16 1We were not using the corpus’ date metadata for this exercise
- 17. Corpus Cartography • Lexical extraction (of relevant sequences) • Clustering based on similarity measures • Visual representation (map of the corpus) based on layout algorithms 17
- 18. Cartography tool: CorText • CorText Manager covers all cartography steps: – Lexical extraction – Clustering – Visualization • Each step can be used independently, thanks to standard import/export formats 18
- 19. ToolscombinedwithCorText CARTOGRAPHY STEP TOOLS and RESOURCES Lexical Extraction DBpedia Spotlight YaTeA Human domain-expert Clustering CorText Analysis Visualization Gephi + Sigma JS plugin - Static CorText MapExplorer Inkscape - Dynamic CorText Heatmaps, Tubes, Distant Reading 19
- 20. Outline • UCL Bentham Project & Transcribe Bentham • How navigate this corpus? Visualizations – Lexical extraction – Co-occurrence networks • Static view and Temporal evolution • Evaluation and Challenges • Other corpus explorations via visualization • Distant Reading Module, WordTree • Other lexical analyses 20
- 21. Lexical Extraction • CorText native option – Noun-Phrase chunks (based on TreeTagger) • Our options: – Entity Linking / Wikification to DBpedia – Keyphrase extraction tools like YaTeA • In all cases: manual selection of pre-ranked candidate terms by a domain-expert 21
- 22. Entity Linking / Wikification • Given a database with encyclopedic knowledge (e.g. Wikipedia) - Finds references (mentions) to DB terms in text - Dealing with variability in the mentions for a term 22
- 23. Entity Linking / Wikification • Given a database with encyclopedic knowledge (e.g. Wikipedia) - Finds references (mentions) to DB terms in text - Dealing with variability in the mentions for a term 23 Database
- 24. Entity Linking / Wikification • Given a database with encyclopedic knowledge (e.g. Wikipedia) - Finds references (mentions) to DB terms in text - Dealing with variability in the mentions for a term 24 Database
- 25. Entity Linking / Wikification • Given a database with encyclopedic knowledge (e.g. Wikipedia) - Finds references (mentions) to DB terms in text - Dealing with variability in the mentions for a term 25 DatabaseCorpus - judicatory - judicial - judicature - Judicatory - Judicial
- 26. Entity Linking / Wikification • Tool: DBpedia Spotlight • Compares the context of sequences of words in a text against DBpedia articles: – Term definition’s text – Links – DBpedia structure (redirections etc.) • Assigns a DBpedia term to the sequence if a good match is found 26
- 27. Entity Linking / Wikification Example terms and their variants 27 Term Variants Judiciary judicature, judicatory, judicial Jury jury, juries Monarch king, monarch Quantity amount, quantity Saint Peter Simon Peter, Cephas
- 28. Entity Linking / Wikification 28 • Applying a current knowledge-base (DBpedia) to 18th-19th century texts • Is this a valid method?
- 29. Keyphrase extraction • YaTeA (Aubin and Hamon, 2006) • Extracts noun-phrases of configurable structure and length 29
- 30. Outline • UCL Bentham Project & Transcribe Bentham • How navigate this corpus? Visualizations – Lexical extraction – Co-occurrence networks • Static view and Temporal evolution • Evaluation and Challenges • Other corpus explorations via visualization • Distant Reading Module, WordTree • Other lexical analyses 30
- 31. Clustering • CorText offers several similarity metrics – we chose the default method (distributional) for homogeneous networks (Weeds & Weir 2005) 31
- 32. Visualization • Static (one map for all dated transcripts) • Dynamic: temporal slices on the corpus – Heatmaps – “River” or Sankey networks (“Tubes layout”) 32 http://apps.lattice.cnrs.fr/bentham
- 33. Static visualization 33 CorText network visualized with Gephi
- 34. Static visualization 34 CorText network visualized with Gephi
- 37. Example term: happiness 37 CorText network made interactive thanks to Gephi’s Sigma JS Exporter
- 44. Examples: nodes linking clusters 44
- 45. Examples: nodes linking clusters 45
- 46. Heatmaps: Saliency per subcorpus 46
- 50. Dynamic visualization 50 1795 1800 1805 1810
- 51. Dynamic visualization 51 1795 1800 1805 1810
- 52. Dynamic visualization 52 1795 1800 1805 1810
- 53. Dynamic visualization 53 1795 1800 1805 1810
- 54. Outline • UCL Bentham Project & Transcribe Bentham • How navigate this corpus? Visualizations – Lexical extraction – Co-occurrence networks • Static view and Temporal evolution • Evaluation and Challenges • Other corpus explorations via visualization • Distant Reading Module, WordTree • Other lexical analyses 54
- 55. Evaluation • Static maps: terms in the clusters correspond closely to issues dealt with by Bentham for the thematic areas of each cluster • Heatmaps: The evolution depicted corresponds to the evolution of topics in Bentham’s work • DBpedia vs. keyphrase extraction: The keyphrases provide more relevant evidence for specialized scholars, a general encyclopedia can help other users 55
- 57. Challenges Thematic Variety • Animal Welfare • Arts • Capital punishment • Civil Code • Constitutional Code • Convict transportation • Correspondence • Crime & Punishment • Education • Law • Legislation • Moral Philosophy • New South Wales • Panopticon • Penal Code • Political Economy • Preventive Police • Religion • Science • Sexual Morality • Torture Formal Variety • Text sheets • Copies / Fair copies • Marginal summary sheets • Correspondence • Collectanea • Rudiments • Spencers 57 From http://www.transcribe-bentham.da.ulcc.ac.uk/td/Manuscripts and http://www.benthampapers.ucl.ac.uk/help.aspx?subject=category
- 58. Outline • UCL Bentham Project & Transcribe Bentham • How navigate this corpus? Visualizations – Lexical extraction – Co-occurrence networks • Static view and Temporal evolution • Evaluation and Challenges • Other corpus explorations via visualization • Distant Reading Module, WordTree • Other lexical analyses 58
- 59. Distant Reading Module • Follow evolution of selected lexical sequences 59
- 60. Evolution of a lexical item 60 Temporal evolution Temporal evolution profiles: - Here: Rising, but present at all dates - Other examples: falling, regular spikes etc.
- 64. Context evolution: Bump Charts 64 • Example: evil
- 67. • Example: relations among neighbours of evil Relations in the context: Egonetworks 67
- 68. Evolution of neighbours’ relations 68 Egonetworks(Period2)
- 69. Evolution of neighbours’ relations 69 Egonetworks(Period3)
- 70. Evolution of neighbours’ relations 70 Egonetworks(Period4)
- 71. Outline • UCL Bentham Project & Transcribe Bentham • How navigate this corpus? Visualizations – Lexical extraction – Co-occurrence networks • Static view and Temporal evolution • Evaluation and Challenges • Other corpus explorations via visualization • Distant Reading Module, WordTree • Other lexical analyses 71
- 72. Other Lexical Analyses • TXM “textometry” tool – Automatic part-of- speech tagging – Partition texts according to metadata – Query corpus using linguistic criteria – Statistical analyses (overrepresentation, underrepresentation) 72 [ http://textometrie.ens-lyon.fr/?lang=en ]
- 73. Lexical Analysis with TXM 73
- 74. Lexical Analysis with TXM • Partition the corpus according to Category, Year, Decade, Main headings, or other available metadata 74
- 75. Lexical Analysis with TXM Number of words per Category 75
- 76. Lexical Analyses with TXM • Over- (or under-) representation of given words per decade (after partitioning per decade) 76
- 77. TXM linguistic queries • Evil followed by a noun, per text-category 77
- 78. TXM linguistic queries • Sentences containing an adjective + evil 78
- 79. Summary • Accessing a large unedited corpus – Cartography methods • Lexical extraction • Maps – Static picture of the corpus – Temporal evolution – Other visualizations (Distant, WordTree) • Domain-expert feedback • Challenges • Other lexical analyses 79 http://apps.lattice.cnrs.fr/bentham
- 80. Bibliography Aubin, S., and Hamon, T. (2006) Improving Term Extraction with Terminological Resources. In Advances in Natural Language Processing: 5th International Conference on NLP, FinTAL 2006, pp. 380-387. LNAI 4139. Springer. Auer, Sören, et al. (2007). DBpedia: A nucleus for a web of open data. The Semantic Web. Springer. Causer, Tim, and Terras, Melissa (2014a). Many hands make light work. Many hands together make merry work: Transcribe Bentham and crowdsourcing manuscript collections, in Crowdsourcing Our Cultural Heritage, ed. M. Ridge, Ashgate Causer, Tim, and Terras, Melissa (2014b). Crowdsourcing Bentham: Beyond the Traditional Boundaries of Academic History, International Journal of Humanities and Arts Computing, 8 Chavalarias, David, and Jean-Philippe Cointet. (2013). Phylomemetic Patterns in Science Evolution—The Rise and Fall of Scientific Fields. PLoS ONE 8 (2) Cortext Manager Documentation (2016). https://docs.cortext.net/. Mendes, Pablo N., Max Jakob, Andrés García-Silva, and Christian Bizer. (2011). DBpedia Spotlight: Shedding Light on the Web of Documents. In Proceedings of the 7th International Conference on Semantic Systems, 1–8. ACM. Mélanie, F., Tieberghien, E., Ruiz, P., Poibeau, T., Causer, T. Terras, M. (2016). Mapping the Bentham Corpus. In Digital Humanities Conference (DH 2016). Kraków, Poland. Poibeau, T. and Ruiz, P. (2015). Generating Navigable Semantic Maps from Social Sciences Corpora. In Digital Humanities Conference (DH 2015). Sydney, Australia. Rule, Alix, Jean-Philippe Cointet, and Peter S. Bearman. (2015). Lexical Shifts, Substantive Changes, and Continuity in State of the Union Discourse, 1790–2014. Proceedings of the National Academy of Sciences 112 (35) Venturini, T., N. Baya Laffite, J.-P. Cointet, I. Gray, V. Zabban, and K. De Pryck. (2014). Three Maps and Three Misunderstandings: A Digital Mapping of Climate Diplomacy. Big Data & Society 1 Weeds J, Weir D (2005). Co-occurrence retrieval: A flexible framework for lexical distributional similarity. In Computational Linguistics 31(4), 439–475. Wattenberg, M. and Viégas, F.B., 2008. The word tree, an interactive visual concordance. In IEEE transactions on visualization and computer graphics, 14(6), pp.1221-1228. 80
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- 82. 82 & return you all due thanks pablo.ruiz.fabo@ens.fr http://www.lattice.cnrs.fr/Pablo-Ruiz-Fabo,541 http://apps.lattice.cnrs.fr/