‘Voyant Tools’

‘Voyant Tools’

Introduction: Digital humanists looking for tools in order to visualize and analyze texts can rely on ‘Voyant Tools’ (https://voyant-tools.org), a software package created by S.Sinclair and G.Rockwell. Online resources are available in order to learn how to use Voyant. In this post, we highlight two of them: “Using Voyant-Tools to Formulate Research Questions for Textual Data” by Filipa Calado (GC Digital Fellows and the tutorial “Investigating texts with Voyant” by Miriam Posner.

Evaluating named entity recognition tools for extracting social networks from novels

Evaluating named entity recognition tools for extracting social networks from novels

Introduction: Named Entity Recognition (NER) is used to identify textual elements that gives things a name. In this study, four different NER tools are evaluated using a corpus of modern and classic fantasy or science fiction novels. Since NER tools have been created for the news domain, it is interesting to see how they perform in a totally different domain. The article comes with a very detailed methodological part and the accompanying dataset is also made available.

From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources

From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources

Introduction: This lesson by Marten Düring from the “Programming Historian-Website” gently introduces novices to the topic to Network Visualisation of Historical Sources. As a case study it covers not only the general advantages of network visualisation for humanists but also a step-by-step explanation of the process from extraction of the data until the visualization (using the Palladio-tool). This lesson has also been translated into Spanish and includes many useful references for further reading.

Towards Scientific Workflows and Computer Simulation as a Method in Digital Humanities – Digitale Bibliothek – Gesellschaft für Informatik e.V.

Introduction: The explore! project tests computer stimulation and text mining on autobiographic texts as well as the reusability of the approach in literary studies. To facilitate the application of the proposed method in broader context and to new research questions, the text analysis is performed by means of scientific workflows that allow for the documentation, automation, and modularization of the processing steps. By enabling the reuse of proven workflows, the goal of the project is to enhance the efficiency of data analysis in similar projects and further advance collaboration between computer scientists and digital humanists.

Attributing Authorship in the Noisy Digitized Correspondence of Jacob and Wilhelm Grimm | Digital Humanities

Attributing Authorship in the Noisy Digitized Correspondence of Jacob and Wilhelm Grimm | Digital Humanities

Introduction: Apart from its buoyant conclusion that authorship attribution methods are rather robust to noise (transcription errors) introduced by optical character recognition and handwritten text recognition, this article also offers a comprehensive read on the application of sophisticated computational techniques for testing and validation in a data curation process.