visualisation

Queen Victoria’s Handwriting and State Papers Deciphered by AI-driven Transcription Solution

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A montage of images of sources from State Papers Online: Nineteenth Century: The State Papers of Queen Victoria and King Edward VII combined with a photograph of Queen Victoria taken in 1882, available in Wikimedia Commons

|By Paul Schummer – Senior Manager, Gale Content Production, and Chris Houghton – Head of Academic Partnerships|

We often use tools without understanding how they work. Chris, for example, has a hazy memory of learning how a vacuum cleaner works in a school physics lesson, but if you asked him to explain it now, he’d struggle! Most of the time, that’s fine – it’s why we take our car to a garage rather than learning how to fix it ourselves. So it’s understandable that researchers or students working with databases might not know how these collections came to be, and what is actually happening when they run a search. However, to be a truly effective researcher, it’s important to understand how these databases work, so that you can adapt your investigations and not miss vital information that is significant to your scholarship. 

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Uncovering New Angles and Arguments with Text Mining

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│By Georgia Platt, Gale Ambassador at Lancaster University│

Six months ago, I knew nothing about Digital Humanities or text mining. It wasn’t really a topic covered in my undergraduate degree in History, and I’d always been a bit unsure of the place technology has in historical research. Then I began my MA in Digital Humanities, which I chose to try and engage with these technological aspects of humanities studies that I hadn’t had the opportunity to explore before. I spent the first ten weeks of this course doing an intensive text mining module, and it revolutionised my approach to historical study.

If you’re curious about text mining but don’t know where to start, or are a digital humanities sceptic looking to be proved wrong, this blog post is for you. I will start with some basic theory of what text mining is and what kinds of questions it can answer, then I’ll put my practical skills to the test with an example from my studies in Victorian crime and punishment.

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Women’s History Month in Gale Digital Scholar Lab: Named Entity Recognition, Python Notebooks, and an Intrepid Female Diarist

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│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

Every March is Women’s History Month! In keeping with the themes of digital scholarship explored in the ‘Notes from our DH Correspondent’ series, and to celebrate a lesser-known historical female figure, in this month’s post I’ll discuss how I am exploring some of my text research data using a new enhancement to Gale Digital Scholar Lab’s embedded analysis pathways.

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Digging into Parts-of-Speech Tagging in Gale Digital Scholar Lab

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Notes from our DH Correspondent

│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

Continuing our exploration of the digital tools accessible through Gale Digital Scholar Lab’s intuitive interface, the Parts-of-Speech (PoS) tool enables the researcher to gain granular insights into the different parts of speech used in each document in a content set. This post will highlight the main features of the tool and provide tips about setup and options for displaying and refining analysis results. We’ll wrap up with a few examples of this quantitative analysis method used in research projects and publications.

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Exploring Named Entity Recognition in Gale Digital Scholar Lab

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│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

One of six embedded tools in Gale Digital Scholar Lab, Named Entity Recognition (NER) processes Optical Character Recognition (OCR) text data and captures information about a range of words defined as ‘entities’, detailed below. The tool is ideally suited for text-based analysis, including text encoding and mapping. This blog post will discuss some of the highlights of the Lab’s NER tool, and things to bear in mind when creating an analysis configuration. We’ll finish with a couple of sample use cases to inspire your own NER analysis.

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Re-imagining Assignments in the DH Classroom II: Timelines, Digital Exhibits, and Maps

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│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

This is a follow-up blog post to last month’s overview of working with Storymaps in the DH classroom.  We will consider a few more ways to engage students in the creative and intellectually rigorous process of building Digital Humanities projects, conducting analyses, and demonstrating the outcomes of a quarter or semester’s-worth of work. Developing timelines, exhibits and maps involves making use of Gale Digital Scholar Lab’s export functionality, which includes the ability to download:

  • The OCR text output of up to 5,000 documents in any given content set.
  • The full metadata of a content set, up to 10,000 documents.
  • Individual document images.
  • Analysis visualisations in multiple image formats.
  • Analysis raw data in CSV or JSON formats.
  • Documentation and records completed using the Notebook feature, in multiple text formats.

This exported information can then be used as the underlying data for a variety of interactive and public-facing student assignments. 

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Uncovering the Betrayal of J. Robert Oppenheimer with Gale Primary Sources

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│By Nicolas Turner, Gale Ambassador at Leiden University│

The release this year of Christopher Nolan’s Oppenheimer biopic has focused attention on the ‘Red Scare’ of the early 1950s in the United States, a period of history filled with all the ingredients of a thriller: double agents, secret recordings, and dramatic revelations. As Nolan’s film reminds us, however, there was also a very real human cost to the persecutions, with – in the words of the historian Ellen Schrecker – an impact on “the lives of thousands of people”.1

I have always been fascinated by this McCarthyite moment, in which the tide of history seemed to suddenly go out, leaving people stranded with beliefs that had previously been acceptable but were now framed as treasonous or worse. I was therefore thrilled to discover in Gale’s Political Extremism and Radicalism archive a treasure trove of documents that offered direct access to the experiences of those living through that dramatic moment – including, most tantalisingly of all, J. Robert Oppenheimer himself.

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Re-imagining Assignments in the DH Classroom: StoryMaps

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│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

It’s back-to-school season, and the next two ‘Notes from Our DH Correspondent’ blog posts will focus on non-traditional assignments in the DH classroom. Often, Humanities classes culminate in a final paper or essay which is a worthwhile exercise in sifting through relevant information to answer a question or propose a thesis. A syllabus that incorporates Digital Humanities methodologies, however, often blends subject content with technical and analytic proficiencies, meaning an essay may not be the best medium to showcase student learning in this scenario. Below we consider tools for digital storytelling which blend text, image, and analysis results to create engaging and interactive assignment outputs.

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Understanding Recent Enhancements to Sentiment Analysis in Gale Digital Scholar Lab

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│By Sarah L. Ketchley, Senior Digital Humanities Specialist│

Sentiment Analysis can be described as an exploratory form of analysis that reveals trends or patterns in positive, negative or neutral sentiment of a collected set of documents (a ‘Content Set’). This type of analysis can identify avenues for further research or investigation at both a macro (Content Set) and micro (document) level.2 Sentiment Analysis is one of the six analysis tools available in Gale Digital Scholar Lab where it was recently updated to include an expanded sentiment lexicon which offers opportunities to further refine analysis results. This blog post will discuss these enhancements and offer suggested pathways to work with Sentiment Analysis both in the classroom and for research.

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ECCO’ing through the Ages: Exploring Reception with Gale’s Eighteenth Century Collections Online

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Reception Reader showing reuses of Shaftesbury’s A Letter Concerning Enthusiasm; overlaps with Astell’s An Enquiry After Wit highlighted by a red box.

│By David Rosson, Doctoral Researcher at the University of Helsinki│

A big-picture goal for the Computational History research group at the University of Helsinki is to develop methods for studying how ideas spread during the Age of Enlightenment. This was a time period marked by notable thinkers and burgeoning ideas about reason, science, human nature, the state, and society as a system operating on certain principles. These ideas have profoundly shaped the modern world we live in today and in many ways still bear influence on current affairs.

An indispensable resource for studying historical discourse in this period is Gale’s Eighteenth Century Collections Online (ECCO), which covers a considerable portion of books published in Britain between 1700 and 1800. Our research group has been working with the datasets and building research infrastructure on top of Gale’s primary sources for more than a decade. One of the latest examples of our researcher-oriented tools is a web interface, Reception Reader, that helps with the tasks of exploring text reuse patterns in ECCO documents.3

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