13 research outputs found
Summarizing text to embed qualitative data into visualizations
Qualitative data can be conveyed with strings of text. Fitting longer text
into visualizations requires a) space to place the text inside the
visualization; and b) appropriate text to fit the space available. For
quantitative visualizations, space is available in area marks; or within
visualization layouts where the marks have an implied space (e.g. bar charts).
For qualitative visualizations, space is defined in common text layouts such as
prose paragraphs. To fit text within these layouts is a function for emerging
NLP capabilities such as summarization.Comment: 6 pages, 8 figures, accepted at NLVIZ 2022: Exploring Research
Opportunities for Natural Language, Text, and Data Visualizatio
An AI-Resilient Text Rendering Technique for Reading and Skimming Documents
Readers find text difficult to consume for many reasons. Summarization can
address some of these difficulties, but introduce others, such as omitting,
misrepresenting, or hallucinating information, which can be hard for a reader
to notice. One approach to addressing this problem is to instead modify how the
original text is rendered to make important information more salient. We
introduce Grammar-Preserving Text Saliency Modulation (GP-TSM), a text
rendering method with a novel means of identifying what to de-emphasize.
Specifically, GP-TSM uses a recursive sentence compression method to identify
successive levels of detail beyond the core meaning of a passage, which are
de-emphasized by rendering words in successively lighter but still legible gray
text. In a lab study (n=18), participants preferred GP-TSM over pre-existing
word-level text rendering methods and were able to answer GRE reading
comprehension questions more efficiently.Comment: Conditionally accepted to CHI 202
Interactive Visual Alignment of Medieval Text Versions
Textual criticism consists of the identification and analysis of variant readings among different versions of a text. Being a relatively simple
task for modern languages, the collation of medieval text traditions ranges from the complex to the virtually impossible depending on the degree of instability of textual transmission. We present a visual analytics environment that supports computationally aligning such complex textual differences typical of orally inflected medieval poetry. For the purpose of analyzing alignment, we provide interactive visualizations for different text hierarchy levels, specifically, a meso
reading view to support investigating repetition and variance at the line level across text segments. In addition to outlining important
aspects of our interdisciplinary collaboration, we emphasize the utility of the proposed system by various usage scenarios in medieval French literature
Text in Visualization: Extending the Visualization Design Space
This thesis is a systematic exploration and expansion of the design space of data visualization specifically with regards to text. A critical analysis of text in data visualizations reveals gaps in existing frameworks and the use of text in practice. A cross-disciplinary review across fields such as typography, cartography and technical applications yields typographic techniques to encode data into text and provides the scope for the expanded design space. Mapping new attributes, techniques and considerations back to well understood visualization principles organizes the design space of text in visualization. This design space includes: 1) text as a primary data type literally encoded into alphanumeric glyphs, 2) typographic attributes, such as bold and italic, capable of encoding additional data onto literal text, 3) scope of mark, ranging from individual glyphs, syllables and words; to sentences, paragraphs and documents, and 4) layout of these text elements applicable most known visualization techniques and text specific techniques such as tables. This is the primary contribution of this thesis (Part A and B).
Then, this design space is used to facilitate the design, implementation and evaluation of new types of visualization techniques, ranging from enhancements of existing techniques, such as, extending scatterplots and graphs with literal marks, stem & leaf plots with multivariate glyphs and broader scope, and microtext line charts; to new visualization techniques, such as, multivariate typographic thematic maps; text formatted to facilitate skimming; and proportionally encoding quantitative values in running text – all of which are new contributions to the field (Part C). Finally, a broad evaluation across the framework and the sample visualizations with cross-discipline expert critiques and a metrics based approach reveals some concerns and many opportunities pointing towards a breadth of future research work now possible with this new framework. (Part D and E)