"It's just a graph"– The Effect of Post-Hoc Rationalisation on InfoVis Evaluation
A growing body of work in InfoVis explores its user experience (UX), however, emotions remain underexplored. Our study reveals barriers for investigating personal connection and emotional reaction to visualisations. This provides an explanation for why the role of emotions so far received little attention in InfoVis. Twenty-four participants viewed two traditional data visualisations, answered UX questionnaires for each, and were interviewed about their experience. Our findings show that traditional visualisations are seen as ‘just a graph’, that represents neutral information. Participants referred to aesthetics, legibility, and usability, instead of the actual topic. Moreover, to make sense of the data, emotions have to be separated from it. We found four possible explanations underlying this belief and argue that a form of post-hoc rationalisation takes place, which obscures people’s initial connections and affective responses to visualisations. Based on these findings, we discuss implications for future research on the UX of visualisations.
Research Questions / Practical Problems
Question signals indexed for this paper.
- 75%
TopoText: Context-Preserving Text Data Exploration Across Multiple Spatial Scales
CHI '18· Interactive Data Visualization +1
- 75%
Truncating the Y-Axis: Threat or Menace?
CHI '20· Interactive Data Visualization +1
- 75%
Data-Driven Mark Orientation for Trend Estimation in Scatterplots
CHI '21· Interactive Data Visualization +1
- 75%
reVISit: Looking Under the Hood of Interactive Visualization Studies
CHI '21· Interactive Data Visualization +1
- 75%
DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data Preparation
CHI '23· Interactive Data Visualization +1
- 75%
VAID: Indexing View Designs in Visual Analytics System
CHI '24· Interactive Data Visualization +1
- 75%
Intra, Extra, Read all about it! How Readers Interpret Visualizations with Intra- and Extratextual Information
CHI '25· Interactive Data Visualization +1
- 75%
PriorWeaver: Prior Elicitation via Iterative Dataset Construction
CHI '26· Interactive Data Visualization +1
- 75%
Taking Truncation to Task: A Task-Based Exploration of Axis Truncation in Bar Charts
CHI '26· Interactive Data Visualization +1
- 75%
D-MO: Depth from Motion and Occlusion as a Visual Channel for Information Visualization
CHI '26· Interactive Data Visualization +1
Based on Jaccard similarity of research subtopics & professions (≥60%)