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LaDawn Jentzsch

dblp:130/0362 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
eye-tracking
0.212013
Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts · WWW 2013
Information retrieval › user behavior
mouse movement analysis
0.212013
Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts · WWW 2013
Information retrieval › interactive information retrieval
search result examination
0.212013
Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts · WWW 2013
Information retrieval › interactive information retrieval
search result interaction
0.212013
Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts · WWW 2013

Methods — techniques the papers use, named apart from their topics

mouse tracking · 0.2eye tracking · 0.2
YearPublicationVenuePosition
2013 Measurement and modeling of eye-mouse behavior in the presence of nonlinear page layouts
abstract
As search pages are becoming increasingly complex, with images and nonlinear page layouts, understanding how users examine the page is important. We present a lab study on the effect of a rich informational panel to the right of the search result column, on eye and mouse behavior. Using eye and mouse data, we show that the flow of user attention on nonlinear page layouts is different from the widely believed top-down linear examination order of search results. We further demonstrate that the mouse, like the eye, is sensitive to two key attributes of page elements -- their position (layout), and their relevance to the user's task. We identify mouse measures that are strongly correlated with eye movements, and develop models to predict user attention (eye gaze) from mouse activity. These findings show that mouse tracking can be used to infer user attention and information flow patterns on search pages. Potential applications include ranking, search page optimization, and UI evaluation.
Vidhya Navalpakkam, LaDawn Jentzsch, Rory Sayres, Sujith Ravi, Amr Ahmed 0001, Alexander J. Smola
WWW2