Research COVID-19 with AVOBMAT

Research COVID-19 with AVOBMAT

Introduction: In our guidelines for nominating content, databases are explicitly excluded. However, this database is an exception, which is not due to the burning issue of COVID-19, but to its exemplary variety of digital humanities methods with which the data can be processed.AVOBMAT makes it possible to process 51,000 articles with almost every conceivable approach (Topic Modeling, Network Analysis, N-gram viewer, KWIC analyses, gender analyses, lexical diversity metrics, and so on) and is thus much more than just a simple database – rather, it is a welcome stage for the Who is Who (or What is What?) of OpenMethods.

‘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.

Not All Character N-grams Are Created Equal: A Study in Authorship Attribution – ACL Anthology

Introduction: Studying n-grams of characters is today a classical choice in authorship attribution. If some discussion about the optimal length of these n-grams have been made, we have still have few clues about which specific type of n-grams are the most helpful in the process of efficiently identifying the author of a text. This paper partly fills that gap, by showing that most of the information gained from studying n-grams of characters comes from the affixes and punctuation.

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.