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<h3><a href="https://vimeo.com/groups/vis18previews/videos/289785167" rel="nofollow">Video Preview</a> | <a href="https://www.eg.bucknell.edu/~emp017/papers/patterns-and-pace-vis2018.pdf" rel="nofollow">Paper Link</a></h3> <h3>Patterns and Pace: Quantifying Diverse Exploration Behavior with Visualizations on the Web</h3> <p>This data and analyses accompany the following forthcoming paper: </p> <p><em>To Appear:</em> Mi Feng, Evan M. Peck, and Lane Harrison. Patterns and Pace: Quantifying Diverse Exploration Behavior with Visualizations on the Web. <em>IEEE TVCG: Transactions on Visualization and Computer Graphics (InfoVis 2018)</em></p> <h4>Paper Abstract</h4> <p>The diverse and vibrant ecosystem of interactive visualizations on the web presents an opportunity for researchers and practitioners to observe and analyze how everyday people interact with data visualizations. However, existing metrics of visualization interaction behavior used in research do not fully reveal the breadth of peoples’ open-ended explorations with visualizations. One possible way to address this challenge is to determine high-level goals for visualization interaction metrics, and infer corresponding features from user interaction data that characterize different aspects of peoples’ explorations of visualizations. In this paper, we address this challenge by identifying needs for visualization behavior analysis, and by developing corresponding candidate features that can be inferred from users’ interaction data with visualization. We then propose metrics that capture novel aspects of peoples’ open-ended explorations, including exploration uniqueness and exploration pacing. We evaluate these metrics along with four other metrics recently proposed in visualization literature by applying them to interaction data from prior visualization studies. The results of these evaluations suggest that these new metrics 1) reveal new characteristics of peoples’ use of visualizations, 2) can be used to evaluate statistical differences between visualization designs, and 3) are statistically independent of prior metrics used in visualization research. We discuss implications of these results for future studies, including the potential for applying these metrics in visualization interaction analysis, as well as emerging challenges in developing a design space of metrics for visualization engagement.</p> <h3>Data</h3> <p>The data files are in the <code>data</code> folder. - Four data files of participants' visit log end with <code>-per-visit.csv</code>, including <em>searchinvis-255-per-visit.csv</em>, <em>searchinvis-boardrooms-per-visit.csv</em> <em>hindsight-255-per-visit.csv</em> and <em>hindsight-metafilter-per-visit.csv</em>. Each row represents a participant's visit to a visual element. and has the following attributes: - <code>id</code> Participant index. - <code>condition</code> (<code>if_search_factor</code>) Participant groups. - <code>chart</code> The name of the visual element visited. - <code>code</code> The code of the visual element visited. - <code>start</code> Start moment of the visit. - <code>end</code> End moment of the visit. - <code>duration</code> Duration of the visit. - <code>time_elapse_from_start</code> Time span from the participant's start of exploration to the start of the visit. - Four data files of participants' groups and exploration time, end with <code>-per-participant.csv</code>, including <em>searchinvis-255-per-participant.csv</em>, <em>searchinvis-boardrooms-per-participant.csv</em> <em>hindsight-255-per-participant.csv</em> and <em>hindsight-metafilter-per-participant.csv</em>.Each row represents a participant. and has the following attributes: - <code>condition</code> (<code>if_search_factor</code>) Participant groups. - <code>time_diff_exploration</code> Exploration time. - Three files of the data elements in the visualizations, start with <code>chart-</code>, including <em>chart-255.csv</em>, <em>chart-metafilter.csv</em>, and <em>chart-baordrooms.csv</em>. Each row represents a visual element. and has the following attributes: - <code>code</code> Chart code. - <code>name</code> Chart name. - <code>x</code>and <code>y</code>: X- and Y-position in the visualization.</p> <h3>Analysis Scripts</h3> <p>The analysis scripts are in the <code>analysis</code> folder, including <em>analysis-searchinvis.rmd</em>, <em>analysis-hindsight.rmd</em> and <em>analysis.R</em> containing the helper functions.</p> <h3>Appendix</h3> <p>The appendix files are in the <code>appendix</code> folder. There are two maps illustrating each new metric using one experiment dataset, including <em>searchinvis-255-exploration-uniqueness.png</em> and <em>searchinvis-255-exploration-pacing.png</em></p>
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