Mental Models, Visual Reasoning and Interaction in Information Visualization: A Top-down Perspective
By Zhicheng Liu, John T. Stasko. IEEE Transactions on Visualization and Computer Graphics, 2010
295 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems
View Paper: https://www.semanticscholar.org/paper/162bd6eadcdebdbc76c39a78c39333b6d763f31f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Computer Vision and Pattern Recognition
- Jessica R. Hullman
- Nicholas A. Diakopoulos
- Zhicheng Liu
- Jeffrey Heer
- Tamara Munzner
- Kevin Crowston
- Ben Shneiderman
- Alan F. Smeaton
In Information Systems
- Jessica R. Hullman
- Nicholas A. Diakopoulos
- Jeffrey Heer
- Bernhard Rieder
- Mark Coddington
- Alina Köchling
- Marius Claus Wehner
Citations in the corpus
- The Effects of Interactive Latency on Exploratory Visual Analysis (2014, background): “• Simulation: subjects perform mental simulations [30, 40] of alternative visual representations not shown in the study to aid the”
- Visualization Rhetoric: Framing Effects in Narrative Visualization (2011, background): “Liu and Stasko [26] frame the site of such differences via the mental model concept, arguing that the effects of such differences on interpretation have been underexplored in InfoVis.”
- Explaining the Gap: Visualizing One's Predictions Improves Recall and Comprehension of Data (2017, background): “Close studies of visualization comprehension indicate that users’ interactions with their internal representations —mental models of what they know and are learning about a dataset—of the data are critical to the interpretation process [6, 20, 21, 33, 47].”