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.

Cultural Ontologies: the ArCo Knowledge Graph.

Cultural Ontologies: the ArCo Knowledge Graph.

Introduction: Standing for ‘Architecture of Knowledge’, ArCo is an open set of resources developed and managed by some Italian institutions, like the MiBAC (Minister for the Italian Cultural Heritage) and, within it, the ICCD – Institute of the General Catalogue and Documentation), and the CNR – Italian National Research Council. Through the application of eXtreme Design (XD), ArCO basically consists in an ontology network comprising seven modules (the arco, the core, the catalogue, the location, the denotative description, the context description, and the cultural event) and a set of LOD data comprising a huge amount of linked entities referring to the national Italian cultural resources, properties and events. Under constant refinement, ArCo represents an example of a “robust Semantic Web resource” (Carriero et al., 11) in the field of cultural heritage, along with other projects like, just to mention a couple of them, the Google Arts&Culture (https://artsandculture.google.com/) or the Smithsonian American Art Museum (https://americanart.si.edu/about/lod).

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When history meets technology. impresso: an innovative corpus-oriented perspective.

When history meets technology. impresso: an innovative corpus-oriented perspective.

Historical newspapers, already available in many digitized collections, may represent a significant source of information for the reconstruction of events and backgrounds, enabling historians to cast new light on facts and phenomena, as well as to advance new interpretations. Lausanne, University of Zurich and C2DH Luxembourg, the ‘impresso – Media Monitoring of the Past’ project wishes to offer an advanced corpus-oriented answer to the increasing need of accessing and consulting collections of historical digitized newspapers.
[…] Thanks to a suite of computational tools for data extraction, linking and exploration, impresso aims at overcoming the traditional keyword-based approach by means of the application of advanced techniques, from lexical processing to semantically deepened n-grams, from data modelling to interoperability.
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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.

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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.

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Approaching Linked Data

Approaching Linked Data

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.

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

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

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.

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