Visual Text Analysis in Digital Humanities

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: closed (10 October 2021) | Viewed by 17128

Special Issue Editor


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Guest Editor
Institute for Mathematics and Computer Science, University of Southern Denmark, Odense, Denmark
Interests: information visualization; visualization in applications; digital humanities; text visualization; geovisualization

Special Issue Information

Dear Colleagues,

Since Franco Moretti introduced the term “distant reading”, visualization as a means to quantitatively analyze textual data has become increasingly important for digital humanities applications in recent years. The utility of visualization to verify and generate hypotheses, and to provide new perspectives on text is well-documented in various publications published in different venues. At the same time, there are many open challenges, for example, concerning the visual analysis of large text corpora or the visualization of textual uncertainties.

This Special Issue seeks contributions reporting on recent advancements concerning visual text analysis from scholars who engage in the context of digital humanities and visualization. This includes novel techniques to visually communicate textual features, as well as the discussion of visual exploration frameworks and visual analytics systems that might bear on or combine well-established visualization techniques, but support textual scholars’ tasks for which no appropriate solutions existed before. Topics of interest include but are not limited to:

  • Digital close reading;
  • Distant readings of text;
  • Corpus analysis;
  • Discourse analysis;
  • News and social media analysis;
  • Translation studies;
  • Textual variation;
  • Text re-use detection and analysis;
  • Digital libraries;
  • Visual depictions of textual uncertainty (fragmentary availability, imprecise OCR, uncertain metadata, authorship attribution, etc.).

In addition to application-driven contributions, this Special Issue also welcomes submissions with extensive reflections on interdisciplinary collaborations between textual scholars and visualization experts. These papers will act as a guide for researchers working on the intersection of digital humanities and visualization, and will be useful for scholars who follow participatory design approaches involving experts from various research domains.

Dr. Stefan Jänicke
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • text visualization
  • close reading visualization
  • distant reading visualization
  • digital humanities
  • visual exploration
  • visual text analysis

Published Papers (5 papers)

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Research

14 pages, 2278 KiB  
Article
Translation Alignment with Ugarit
by Tariq Yousef, Chiara Palladino, Farnoosh Shamsian and Maryam Foradi
Information 2022, 13(2), 65; https://doi.org/10.3390/info13020065 - 27 Jan 2022
Cited by 9 | Viewed by 3664
Abstract
Ugarit is a public web-based tool for manual annotation of parallel texts for generating word-level translation alignment. We aimed to develop a user-friendly interactive interface to visualize aligned texts and collect training data in the form of translation pairs to be used later, [...] Read more.
Ugarit is a public web-based tool for manual annotation of parallel texts for generating word-level translation alignment. We aimed to develop a user-friendly interactive interface to visualize aligned texts and collect training data in the form of translation pairs to be used later, (i) for training an automatic translation alignment system for historical languages at the word/phrase level, (ii) as a gold standard to evaluate automatic alignment and machine translation systems. Ugarit is now widely used for learning new languages, especially historical languages, and as a reading environment for parallel texts. In the following sections, we present the related works and similar projects; then, we give an overview of the visualization techniques used to present the alignment results. Further, we explain how we could derive the translation graph from the aligned translation pairs. Finally, we discuss the usage limitations of Ugarit, possible improvements, and future development plans. Full article
(This article belongs to the Special Issue Visual Text Analysis in Digital Humanities)
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23 pages, 2912 KiB  
Article
Exploring Life in Concentration Camps through a Visual Analysis of Prisoners’ Diaries
by Richard Khulusi, Stephanie Billib and Stefan Jänicke
Information 2022, 13(2), 54; https://doi.org/10.3390/info13020054 - 21 Jan 2022
Cited by 2 | Viewed by 3530
Abstract
Diaries are private documentations of people’s lives. They contain descriptions of events, thoughts, fears, and desires. While diaries are usually kept in private, published ones, such as the diary of Anne Frank, show that they bear the potential to give personal insight into [...] Read more.
Diaries are private documentations of people’s lives. They contain descriptions of events, thoughts, fears, and desires. While diaries are usually kept in private, published ones, such as the diary of Anne Frank, show that they bear the potential to give personal insight into events and into the emotional impact on their authors. We present a visualization tool that provides insight into the Bergen-Belsen memorial’s diary corpus, which consists of dozens of diaries written by concentration camp prisoners. We designed a calendar view that documents when authors wrote about concentration camp life. Different modes support quantitative and sentiment analyses, and we provide a solution for historians to create thematic concepts that can be used for searching and filtering for specific diary entries. The usage scenarios illustrate the importance of the tool for researchers and memorial visitors as well as for commemorating the Holocaust. Full article
(This article belongs to the Special Issue Visual Text Analysis in Digital Humanities)
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18 pages, 1715 KiB  
Article
Explorative Visual Analysis of Rap Music
by Christofer Meinecke, Ahmad Dawar Hakimi and Stefan Jänicke
Information 2022, 13(1), 10; https://doi.org/10.3390/info13010010 - 28 Dec 2021
Cited by 1 | Viewed by 3210
Abstract
Detecting references and similarities in music lyrics can be a difficult task. Crowdsourced knowledge platforms such as Genius. can help in this process through user-annotated information about the artist and the song but fail to include visualizations to help users find similarities and [...] Read more.
Detecting references and similarities in music lyrics can be a difficult task. Crowdsourced knowledge platforms such as Genius. can help in this process through user-annotated information about the artist and the song but fail to include visualizations to help users find similarities and structures on a higher and more abstract level. We propose a prototype to compute similarities between rap artists based on word embedding of their lyrics crawled from Genius. Furthermore, the artists and their lyrics can be analyzed using an explorative visualization system applying multiple visualization methods to support domain-specific tasks. Full article
(This article belongs to the Special Issue Visual Text Analysis in Digital Humanities)
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20 pages, 6183 KiB  
Article
Evaluating a Taxonomy of Textual Uncertainty for Collaborative Visualisation in the Digital Humanities
by Alejandro Benito-Santos, Michelle Doran, Aleyda Rocha, Eveline Wandl-Vogt, Jennifer Edmond and Roberto Therón
Information 2021, 12(11), 436; https://doi.org/10.3390/info12110436 - 21 Oct 2021
Cited by 3 | Viewed by 2313
Abstract
The capture, modelling and visualisation of uncertainty has become a hot topic in many areas of science, such as the digital humanities (DH). Fuelled by critical voices among the DH community, DH scholars are becoming more aware of the intrinsic advantages that incorporating [...] Read more.
The capture, modelling and visualisation of uncertainty has become a hot topic in many areas of science, such as the digital humanities (DH). Fuelled by critical voices among the DH community, DH scholars are becoming more aware of the intrinsic advantages that incorporating the notion of uncertainty into their workflows may bring. Additionally, the increasing availability of ubiquitous, web-based technologies has given rise to many collaborative tools that aim to support DH scholars in performing remote work alongside distant peers from other parts of the world. In this context, this paper describes two user studies seeking to evaluate a taxonomy of textual uncertainty aimed at enabling remote collaborations on digital humanities (DH) research objects in a digital medium. Our study focuses on the task of free annotation of uncertainty in texts in two different scenarios, seeking to establish the requirements of the underlying data and uncertainty models that would be needed to implement a hypothetical collaborative annotation system (CAS) that uses information visualisation and visual analytics techniques to leverage the cognitive effort implied by these tasks. To identify user needs and other requirements, we held two user-driven design experiences with DH experts and lay users, focusing on the annotation of uncertainty in historical recipes and literary texts. The lessons learned from these experiments are gathered in a series of insights and observations on how these different user groups collaborated to adapt an uncertainty taxonomy to solve the proposed exercises. Furthermore, we extract a series of recommendations and future lines of work that we share with the community in an attempt to establish a common agenda of DH research that focuses on collaboration around the idea of uncertainty. Full article
(This article belongs to the Special Issue Visual Text Analysis in Digital Humanities)
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12 pages, 2992 KiB  
Article
Impresso Inspect and Compare. Visual Comparison of Semantically Enriched Historical Newspaper Articles
by Marten Düring, Roman Kalyakin, Estelle Bunout and Daniele Guido
Information 2021, 12(9), 348; https://doi.org/10.3390/info12090348 - 27 Aug 2021
Cited by 8 | Viewed by 2570
Abstract
The automated enrichment of mass-digitised document collections using techniques such as text mining is becoming increasingly popular. Enriched collections offer new opportunities for interface design to allow data-driven and visualisation-based search, exploration and interpretation. Most such interfaces integrate close and distant reading and [...] Read more.
The automated enrichment of mass-digitised document collections using techniques such as text mining is becoming increasingly popular. Enriched collections offer new opportunities for interface design to allow data-driven and visualisation-based search, exploration and interpretation. Most such interfaces integrate close and distant reading and represent semantic, spatial, social or temporal relations, but often lack contrastive views. Inspect and Compare (I&C) contributes to the current state of the art in interface design for historical newspapers with highly versatile side-by-side comparisons of query results and curated article sets based on metadata and semantic enrichments. I&C takes search queries and pre-curated article sets as inputs and allows comparisons based on the distributions of newspaper titles, publication dates and automatically generated enrichments, such as language, article types, topics and named entities. Contrastive views of such data reveal patterns, help humanities scholars to improve search strategies and to facilitate a critical assessment of the overall data quality. I&C is part of the impresso interface for the exploration of digitised and semantically enriched historical newspapers. Full article
(This article belongs to the Special Issue Visual Text Analysis in Digital Humanities)
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