Humanities Data Analysis: Case Studies with Python — Humanities Data Analysis: Case Studies with Python

Humanities Data Analysis: Case Studies with Python — Humanities Data Analysis: Case Studies with Python

Introduction: Folgert Karsdorp, Mike Kestemont and Allen Riddell ‘s  interactive book, Humanities Data Analysis: Case Studies with Python had been written with the aim in mind to equip humanities students and scholars working with textual and tabular resources with practical, hands-on knowledge to better understand the potentials of data-rich, computer-assisted approaches that the Python framework offers to them and eventually to apply and integrate them to their own research projects.

The first part introduces a “Data carpentry”, a collection of essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. This sets the stage for the second part that consists of 5 case studies (Statistics Essentials: WhoReads Novels? ; Introduction to Probability ; Narrating with Maps ; Stylometry and the Voice of Hildegard ; A Topic Model of United States Supreme Court Opinions, 1900–2000 ) showcasing how to draw meaningful insights from data using quantitative methods. Each chapter contains executable Python codes and ends with exercises ranging from easier drills to more creative and complex possibilities to adapt the apply and adopt the newly acquired knowledge to their own research problems.

The book exhibits best practices in how to make digital scholarship available in an open, sustainable ad digital-native manner, coming in different layers that are firmly interlinked with each other. Published with Princeton University Press in 2021, hardcopies are also available, but more importantly, the digital version is an  Open Access Jupyter notebook that can be read in multiple environments and formats (.md and .pdf). The documentation, coda and data materials are available on Zenodo (https://zenodo.org/record/3560761#.Y3tCcn3MJD9). The authors also made sure to select and use packages which are mature and actively maintained.

Collaborative Digital Projects in the Undergraduate Humanities Classroom: Case Studies with Timeline JS

Collaborative Digital Projects in the Undergraduate Humanities Classroom: Case Studies with Timeline JS

https://openmethods.dariah.eu/2022/05/11/open-source-tool-allows-users-to-create-interactive-timelines-digital-humanities-at-a-state/ OpenMethods introduction to: Collaborative Digital Projects in the Undergraduate Humanities Classroom: Case Studies with Timeline JS 2022-05-11 07:28:36 Marinella Testori Blog post Creation Data Designing Digital Humanities English Methods…

The First of May in German Literature

The First of May in German Literature

Introduction by OpenMethods Editor (Erzsébet Tóth-Czifra): Research on date extractions from literature brings us closer to answering big questions of “when literature takes place”.  As Frank Fischer’s blog post, First of May in German literature shows, beyond mere quantification, this line of research also yields insights on the cultural significance of certain dates. In this case, the significance of 1st of May in German literature (as reflected in the “Corpus of German-Language Fiction” dataset) was determined with the help of a freely accessible data set and the open access tool HeidelTime. The brief description of the workflow is a smart demonstration of the potential of open DH methods and data sharing in sustainable ways.

Bonus one: the post starts out from briefly touching upon some of Frank’s public humanities activities.

Bonus two: mention of the Tiwoli (“Today in World Literature”) app, a fun side product built on to pof the date extraction research.

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.

Programmable Corpora: Introducing DraCor, an Infrastructure for the Research on European Drama

Programmable Corpora: Introducing DraCor, an Infrastructure for the Research on European Drama

Introduction: The DraCor ecosystem encourages various approaches to the browsing and consultation of the data collected in the corpora, like those detailed in the Tools section: the Shiny DraCor app (https://shiny.dracor.org/), along with the SPARQL queries and the Easy Linavis interfaces (https://dracor.org/sparql and https://ezlinavis.dracor.org/ respectively). The project, thus, aims at creating a suitable digital environment for the development of an innovative way to approach literary corpora, potentially open to collaborations and interactions with other initiatives thanks to its ontology and Linked Open data-based nature.
[Click ‘Read more’ for the full post!]

Web Scraping with Python for Beginners | The Digital Orientalist

Web Scraping with Python for Beginners | The Digital Orientalist

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.