How We Draw Texts: A Review of Approaches to Text Visualization and Exploration (original) (raw)

How we draw texts: a review of approaches to text visualization and exploration (2014)

2014

"This paper presents a review of approaches to text visualization and exploration. Text visualization and exploration, we ar- gue, constitute a subfield of data visualization, and are fuelled by the advances being made in text analysis research and by the growing amount of accessible data in text format. We propose an original classification for a total of 49 cases based on the visual features of the approaches adopted, identified using an inductive process of analysis. We group the cases (publis- hed between 1994 and 2013) in two categories: single-text visualizations and text-collection visualizations, both of which can be explored and compared online."

Seeing the text through the trees: visualization and interactivity in text applications

Literary and Linguistic Computing, 1999

In this paper we discuss two interactive text visualization systems and then discuss the rhetorical effects of interactivity. The first model is SIMWeb, a data visualization system with connections to TACTweb for full-text searching. SIMWeb provides a graphical representation of the results of statistical processes that can be used to explore a text. The second experiment, Eye-ConTact is a prototype for a process visualization environment for research applications in the study of electronic texts. The paper then discusses the effects of visualization with particular attention to the contribution of interactivity to the process of textual research. We argue that this allows for pragmatic experimentation with processes and information and conclude by discussing some of the dangers of interactive visualization systems.

Interactive text visualization with Text Variation Explorer

Proceedings of the 20th International Conference on Information Visualisation (IV 2016), 2016

Digitalization is changing how research is carried out in all areas of science. Humanities is no exception - materials that used to be hand-written or printed on paper are increasingly available in digital form. This development is changing how scholars are interacting with their material. We are addressing the problem of interactive text visualization in the context of sociolinguistic language study. When a scholar is reading and analyzing text from a computer screen instead of a paper, we can support this by providing a dashboard for reading, and by creating visualizations of the text structure, variation, and change. We have designed and developed a software tool called Text Variation Explorer (TVE) for sociolinguistic language study. It is based on interactive visualization with a direct manipulation user interface, and aimed for exploratory corpus linguistics. The TVE software tool has proven to be useful in supporting the study of language variation and change in its social contexts, or sociolinguistics. It is, to a certain degree, language-independent, and generic enough to be useful in other linguistic contexts as well. We are now in the process of designing and implementing the next iteration of TVE. We present the lessons learned from the first version, discuss the old and the new design, and welcome feedback from the communities involved.

What Shakespeare Taught Us About Text Visualization

2012

In our work we have developed text visualization tools to meet the needs of literary scholars. While our work in this domain may on the surface seem quite different from other text visualization applications, we have encountered principles that generalize and will be useful for text data as distant from literature as social media. The way that digital humanities scholars use and argue about texts are not idiosyncratic to their field: their requirements and rhetoric offer implications for design generally, including renewed focus on outliers, constant connection from visualizations to underlying texts, and the ability to generate explanations for higher level patterns by moving back and forth between these patterns and low-level data.

ViziTex: Interactive Visual Sense-Making of Text Corpora

Proceedings of the Second Workshop on Data Science with Human in the Loop: Language Advances, 2021

Information visualization is critical to analytical reasoning and knowledge discovery. We present an interactive studio that integrates perceptive visualization techniques with powerful text analytics algorithms to assist humans in sense-making of large complex text corpora. The novel visual representations introduced here encode the features delivered by modern text mining models using advanced metaphors such as hypergraphs, nested topologies and tessellated planes. They enhance humancomputer interaction experience for various tasks such as summarization, exploration, organization and labeling of documents. We demonstrate the ability of the visuals to surface the structure, relations and concepts from documents across different domains.

Seeing beyond reading: a survey on visual text analytics

Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2012

We review recent visualization techniques aimed at supporting tasks that require the analysis of text documents, from approaches targeted at visually summarizing the relevant content of a single document to those aimed at assisting exploratory investigation of whole collections of documents. Techniques are organized considering their target input material -either single texts or collections of texts -and their focus, which may be at displaying content, emphasizing relevant relationships, highlighting the temporal evolution of a document or collection, or helping users to handle results from a query posed to a search engine. We describe the approaches adopted by distinct techniques and briefly review the strategies they employ to obtain meaningful text models, how they extract the information required to produce representative visualizations, the tasks they intend to support and the interaction issues involved, as well as strengths and limitations. Finally, we show a summary of techniques, highlighting their goals and distinguishing characteristics. We also briefly discuss some open problems and research directions in the fields of visual text mining and text analytics.