Category: Relational Analysis

Relational Analysis refers to computational techniques serving to discover specific relations between several objects of study. In textual studies, this could mean discovering overlap between several different texts (study of text reuse / plagiarism), or textual variations between several versions of one text (collation), or assessing the similarity of texts in terms of stylistic features (stylometry). By analogy, such methods can also be applied to other cultural artefacts, such as music, film or painting. Relevant techniques include Sequence Alignment, Collation, and techniques associated with Stylistic Analysis.

Analysis

Analyzing Documents with TF-IDF | Programming Historian

Posted on September 15, 2019September 16, 2019
by Rombert Stapel

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.

Analysis

Approaching Linked Data

Posted on August 21, 2019August 22, 2019
by Marinella Testori

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.

Analysis

From Hermeneutics to Data to Networks: Data Extraction and Network Visualization of Historical Sources

Posted on February 28, 2019February 28, 2019
by Ulrike Wuttke

Introduction: This lesson by Marten Düring from the “Programming Historian-Website” gently introduces novices to the topic to Network Visualisation of Historical Sources. As a case study it covers not only the general advantages of network visualisation for humanists but also a step-by-step explanation of the process from extraction of the data until the visualization (using the Palladio-tool). This lesson has also been translated into Spanish and includes many useful references for further reading.

Analysis

Network Visualization with ggplot2

Posted on December 5, 2017April 17, 2018
by Florian CAFIERO

Introduction: This article describes the possibilities offered by the ggplot2 package for network visualization. This R package enables the user to use a wide variety of graphic styles, and to include supplementary information regarding vertices and edges.

Analysis

Towards a Computational Literary Science

Posted on November 16, 2017December 5, 2017
by Francesca Morselli

Introduction: This article introduces a novel way to unfold and discover patterns in complex texts, at the intersection between macro and micro analytics. This technique is called TIC (Transcendental Information Cascades) allows analysis of how a cast of characters is generated and managed dynamically over the duration of a text.