This short blog post by Laure Barbot, Frank Fischer, Yoan Moranville, and Ivan Pozdniakov from 2019 sheds some light on the old question which DH-tools are actually used in research and which are especially popular.
Introduction: In this blog post, James Harry Morris introduces the method of web scraping. Step by step from the installation of the packages, readers are explained how they can extract relevant data from websites using only the Python programming language and convert it into a plain text file. Each step is presented transparently and comprehensibly, so that this article is a prime example of OpenMethods and gives readers the equipment they need to work with huge amounts of data that would no longer be possible manually.
Introduction: Hosted at the University of Lausanne, “A world of possibilities. Modal pathways over an extra-long period of time: the diachrony in the Latin language” (WoPoss) is a project under development exploiting a corpus-based approach to the study and reconstruction of the diachrony of modality in Latin.
Following specific annotation guidelines applied to a set of various texts pertaining to the time span between 3rd century BCE and 7th century CE, the work team lead by Francesca Dell’Oro aims at analyzing the patterns of modality in the Latin language through a close consideration of lexical markers.
The StandforCore NLP wishes to represent a complete Java-based set of tools for various aspects of language analysis, from annotation to dependency parsing, from lemmatization
to coreference resolution. It thus provides a range of tools which
can be potentially applied to other languages apart from English.
Among the languages to which the StandfordCore NLP is mainly applied there is Italian, for which the Tint pipeline has been developed as described in the paper “Italy goes to Stanford: a collection of CoreNLP modules for Italian” by Alessio Palmero Apostolo and Giovanni Moretti.
On the Tint webpage the whole pipeline can be found and downloaded: it comprises tokenization and sentence splitting, morphological analysis and lemmatization, part-of-speech tagging, named-entity recognition and dependency parsing, including wrappers under construction. [Click ‘Read more’ for the whole post.]
Introduction: This white paper is an outcome of a DH2019 workshop dedicated to foster closer collaboration among technology-oriented DH researchers and developers of tools to support Digital Humanities research. The paper briefly outlines the most pressing issues in their collaboration and addresses topics such as: good practices to ease mutual understanding between scholars and researchers; software development and academic career and recognition; or sustainability and funding.
Introduction: Linked Data and Linked Open Data are gaining an increasing interest and application in many fields. A recent experiment conducted in 2018 at Furman University illustrates and discusses some of the challenges from a pedagogical perspective posed by Linked Open Data applied to research in the historical domain.
“Linked Open Data to navigate the Past: using Peripleo in class” by Chiara Palladino describes the exploitation of the search-engine Peripleo in order to reconstruct the past of four archeologically-relevant cities. Many databases, comprising various types of information, have been consulted, and the results, as highlighted in the contribution by Palladino, show both advantages and limitations of a Linked Open Data-oriented approach to historical investigations.
Introduction: Ted Underwood tests a new language representation model called “Bidirectional Encoder Representations from Transformers” (BERT) and asks if humanists should use it. Due to its high degree of difficulty and its limited success (e.g. in questions of genre detection) he concludes, that this approach will be important in the future but it’s nothing to deal with for humanists at the moment. An important caveat worth reading.
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.
Introduction: In this article, Alejandro Bia Platas and Ramón P. Ñeco García introduce TEIdown, an extension of the Markdown syntax that aims at creating XML-TEI documents, and transformation programs. TEIdown helps editors to validate and find errors in TEI documents.
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.