Berkeley Prosopography Services: Building Research Communities and Restoring Ancient Communities through Digital Tools

Berkeley Prosopography Service (BPS) is an innovative open-source digital tool and service that automatically extracts prosopographic data from TEI-encoded text and generates visualizations of the dynamic social networks contained in the text corpora. Filters allow researchers to vary search parameters to consider alternative or hypothetical scenarios such as the impact of individuals and conditions on social and economic relationships. BPS provides users with individual workspaces for research, assessment and probabilistic modelling, while corpus administrators maintain data integrity. During the grant period, BPS, the first independent tool and service to be incorporated into the international Cuneiform Digital Library consortium, will undergo beta-testing of additional text corpora to confirm the reliability and generalizability of its tools for widespread use in the broad community of prosopographers

evoText: A new tool for analyzing the biological sciences

We introduce here evoText, a new tool for automated analysis of the literature in the biological sciences. evoText contains a database of hundreds of thousands of journal articles and an array of analysis tools for generating quantitative data on the nature and history of life science, especially ecology and evolutionary biology. This article describes the features of evoText, presents a variety of examples of the kinds of analyses that evoText can run, and offers a brief tutorial describing how to use it

Image networks and practice analysis of larger data corpora. An approach to cluster and recontextualize visual practice in social media

This paper reports a methodological exploration combining image network analysis and standardized practice analysis on social media data. Through applying the open source software Memespector to access the Clarifai API, the potential of an easy-at-hand image tagging tool as an instrument to manage larger data corpora is explored. Using the example of the German-speaking Twitter hashtag #systemrelevant, we relate image clusters to the results of standardized practice analysis of posts that contain images. The proposed method is intended for research that attempts to carve out the co-constituting of public discourse in social media by different groups of actors. The approach systematically differentiates the contributions of societal groups such as journalism, civil society, or private individuals, and the embedding of their tweets in selected anchoring practices and further modalities of participation. Altogether, the multistep analytical process offers a possible approach to process larger image corpora, while maintaining a sensitivity for the practice-theoretical demand of (re)contextualizing image use

Aspect-Driven Structuring of Historical Dutch Newspaper Archives

Digital libraries oftentimes provide access to historical newspaper archives via keyword-based search. Historical figures and their roles are particularly interesting cognitive access points in historical research. Structuring and clustering news articles would allow more sophisticated access for users to explore such information. However, real-world limitations such as the lack of training data, licensing restrictions and non-English text with OCR errors make the composition of such a system difficult and cost-intensive in practice. In this work we tackle these issues with the showcase of the National Library of the Netherlands by introducing a role-based interface that structures news articles on historical persons. In-depth, component-wise evaluations and interviews with domain experts highlighted our prototype's effectiveness and appropriateness for a real-world digital library collection.Comment: TPDL2023, Full Paper, 16 page

Visual Text Analysis in Digital Humanities

In 2005, Franco Moretti introduced Distant Reading to analyse entire literary text collections. This was a rather revolutionary idea compared to the traditional Close Reading, which focuses on the thorough interpretation of an individual work. Both reading techniques are the prior means of Visual Text Analysis. We present an overview of the research conducted since 2005 on supporting text analysis tasks with close and distant reading visualizations in the digital humanities. Therefore, we classify the observed papers according to a taxonomy of text analysis tasks, categorize applied close and distant reading techniques to support the investigation of these tasks and illustrate approaches that combine both reading techniques in order to provide a multi-faceted view of the textual data. In addition, we take a look at the used text sources and at the typical data transformation steps required for the proposed visualizations. Finally, we summarize collaboration experiences when developing visualizations for close and distant reading, and we give an outlook on future challenges in that research area