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Text Visualization. Marti Hearst Guest Lecture, i247, Spring 2012. Graphing Quantitative Data. Graphing Quantitative Data. Graphing Nominal Data. Preattentive Properties. Text is NOT Preattentive. SUBJECT PUNCHED QUICKLY OXIDIZED TCEJBUS DEHCNUP YLKCIUQ DEZIDIXO
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Text Visualization Marti Hearst Guest Lecture, i247, Spring 2012
Text is NOT Preattentive SUBJECT PUNCHED QUICKLY OXIDIZED TCEJBUS DEHCNUP YLKCIUQ DEZIDIXO CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC GOVERNS PRECISE EXAMPLE MERCURY SNREVOG ESICERP ELPMAXE YRUCREM CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM GOVERNS PRECISE EXAMPLE MERCURY SNREVOG ESICERP ELPMAXE YRUCREM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC SUBJECT PUNCHED QUICKLY OXIDIZED TCEJBUS DEHCNUP YLKCIUQ DEZIDIXO CERTAIN QUICKLY PUNCHED METHODS NIATREC YLKCIUQ DEHCNUP SDOHTEM SCIENCE ENGLISH RECORDS COLUMNS ECNEICS HSILGNE SDROCER SNMULOC
So…. How Do We Visually Represent Content?
“It appeared that the narrative he had promised to read us really required for a proper intelligence a few words of prologue. Let me say here distinctly, to have done with it, that this narrative, from an exact transcript of my own made much later, is what I shall presently give. Poor Douglas, before his death—when it was in sight—committed to me the manuscript that reached him on the third of these days and that, on the same spot, with immense effect, he began to read to our hushed little circle on the night of the fourth.” Henry James, Turn of the Screw
Movies? Georges Méliès Le Voyage dans la Lune (A Trip to the Moon) (1902)
A Comparative Study • Reiterer et al., SIGIR 2000 • Well-done study • They weren’t the creators of the viz’s tested • 40 participants, varied tasks • Compared: • Plain html web page • Sortable search results (in a table view) • Tilebars-like view • Bar charts view • Scatterplot view
A Comparative Study • Reiterer et al., SIGIR 2000 • Results: • People weren’t any better with viz’s than with standard web view. Significantly worse with bar charts • Subjective results: Sortable Table, then Tilebars, then simple web-based view • People disliked the bar charts and scatter plots
Are visual clusters useful? • Four Clustering Visualization Usability Studies • Conclusions: • Huge 2D maps may be inappropriate focus for information retrieval • cannot see what the documents are about • space is difficult to browse for IR purposes • (tough to visualize abstract concepts) • Perhaps more suited for pattern discovery and gist-like overviews.
Clustering Algorithm Problems • Doesn’t work well if data is too homogenous or too heterogeneous • Often is difficult to interpret quickly • Automatically generated labels are unintuitive and occur at different levels of description • Often the top-level can be ok, but the subsequent levels are very poor • Need a better way to handle items that fall into more than one cluster
Creative Facet Visualization • Aduna Autofocus
Creative Facet Visualization • We Feel Fine
Creative Facet Visualization • Fathumb mobile search interface • http://research.microsoft.com/vibe/projects/FaThumb.aspx
Creative Facet Visualization • Hutchinson et al.
Hearst & Rosner, 2007 What’s Up With Tag Clouds?
Definition Tag Cloud: A visual representation of social tags, organized into paragraph-style layout, usually in alphabetical order, where the relative size and weight of the font for each tag corresponds to the relative frequency of its use.
Definition Tag Cloud: A visual representation of social tags, organized into paragraph-style layout, usually in alphabeticalorder, where the relative size and weightofthefont for each tag correspondsto the relative frequency of its use.
