What is PixPlot? (DH Tools) – YouTube

What is PixPlot? (DH Tools) – YouTube

Introduction: This short video teaser summarizes the main characteristics of PixPlot, a Python-based tool for clustering images and analyzing them from a numerical perspective as well as its pedagogical relevance as far as
machine learning is concerned.

The paper “Visual Patterns Discovery in Large Databases of Paintings”, presented at the Digital Humanities 2016 Conference held in Poland,
can be considered the foundational text for the development of the PixPlot Project at Yale University.
[Click ‘Read more’ for the full post!]

BERT for Humanists: a deep learning language model  meets DH

BERT for Humanists: a deep learning language model meets DH

Introduction: Awarded as Best Long Paper at the 2019 NACCL (North American Chapter of the Association for Computational Linguistics) Conference, the contribution by Jacob Devlin et al. provides an illustration of “BERT: Pre-training of Deep Biredictional Transformers for Language Understanding” (https://aclanthology.org/N19-1423/).

As highlighted by the authors in the abstract, BERT is a “new language representation model” and, in the past few years, it has become widespread in various NLP applications; for example, a project exploiting it is CamemBERT (https://camembert-model.fr/), regarding French. 

In June 2021, a workshop organized by David Mimno, Melanie Walsh and Maria Antoniak (https://melaniewalsh.github.io/BERT-for-Humanists/workshop/) pointed out how to use BERT in projects related to digital humanities, in order to deal with word similarity and classification classification while relying on Phyton-based HuggingFace transformers library. (https://melaniewalsh.github.io/BERT-for-Humanists/tutorials/ ). A further advantage of this training resource is that it has been written with sensitivity towards the target audience in mind:  in a way that it provides a gentle introduction to complexities of language models to scholars with education and background other than Computer Science.

Along with the Tutorials, the same blog includes Introductions about BERT in general and in its specific usage in a Google Colab notebook, as well as a constantly-updated bibliography and a glossary of the main terms (‘attention’, ‘Fine-Tune’, ‘GPU’, ‘Label’, ‘Task’, ‘Transformers’, ‘Token’, ‘Type’, ‘Vector’).

What Counts as Culture? Part I: Sentiment Analysis of The Times Music Reviews, 1950-2009 – train in the distance

What Counts as Culture? Part I: Sentiment Analysis of The Times Music Reviews, 1950-2009 – train in the distance

Introduction: This blog post by Lucy Havens presents a sentiment analysis of over 2000 Times Music Reviews using freely available tools: defoe for building the corpus of reviews, VADER for sentiment analysis and Jupiter Notebooks to provide a rich documentation and to connect the different components of the analysis. The description of the workflow comes with tool and method criticism reflections, including an outlook how to improve and continue to get better and more results.

Worthäufigkeiten als Quelle für die Geschichtswissenschaft? – Einblicke in die Digital Humanities

Worthäufigkeiten als Quelle für die Geschichtswissenschaft? – Einblicke in die Digital Humanities

Introduction: Especially humanities scholars (not only historians) who have not yet had any contact with the Digital Humanities, Silke Schwandt offers a motivating and vivid introduction to see the potential of this approach, using the analysis of word frequencies as an example. With the help of Voyant Tools and Nopaque, she provides her listeners with the necessary equipment to work quantitatively with their corpora. Schwandt’s presentation, to which the following report by Maschka Kunz, Isabella Stucky and Anna Ruh refers, can also be viewed at https://www.youtube.com/watch?v=tJvbC3b1yPc.