Topic Modeling mit dem DARIAH Topics Explorer | forTEXT

Topic Modeling mit dem DARIAH Topics Explorer | forTEXT

Introduction: The first steps into working with digital methods of text analysis are often made with beginner-friendly tools. The DARIAH-DE TopicsExplorer opens up the world of topic modeling with an easy-to-understand GUI, numerous operating options and high-quality results. The team of forText of the University of Hamburg developed a tutorial (Lerneinheit) to guide users step by step from installing the software to the first results with a sample corpus. The tutorial also contains screenshots, videos, exercises and explanations. This follows the didactic concept of forText.

Analyzing Documents with TF-IDF | Programming Historian

Analyzing Documents with TF-IDF | Programming Historian

Introduction: The indispensable Programming Historian comes with an introduction to Term Frequency – Inverse Document Frequency (tf-idf) provided by Matthew J. Lavin. The procedure, concerned with specificity of terms in a document, has its origins in information retrieval, but can be applied as an exploratory tool, finding textual similarity, or as a pre-processing tool for machine learning. It is therefore not only useful for textual scholars, but also for historians working with large collections of text.

Teaching Quantitative Methods: What Makes It Hard (in Literary Studies)

Introduction: This article reflects on the lessons learnt by the author as he first taught a graduate course in digital analysis of literary texts. He stresses the importance of methodologies over technologies, the need for well-curated, community-created teaching datasets and the implications of the practical, discipline-based organisation of the curricula.