Data Through Others' Eyes: The Impact of Visualizing Others' Expectations on Visualization Interpretation

Area of Science:

• Human-Computer Interaction
• Data Visualization
• Social Psychology

Background:

• Interactive visualizations can serve as social artifacts, reflecting multiple perspectives on data.
• The impact of embedded social information on data interpretation is not well understood.

Purpose of the Study:

• To evaluate how visualizing others' expectations affects data recall, expectation adjustment, and trust.
• To explore the design space for incorporating social information into data visualizations.

Main Methods:

• A controlled experiment was conducted to assess the effects of social information (others' expectations) on data interpretation.
• Participants' data recall, expectation alignment with data, and trust in data accuracy were measured.

Main Results:

• High consensus in social information improved participants' data recall compared to viewing data alone.
• Participants showed reduced trust in data accuracy and maintained initial expectations when social expectations aligned with their own but not the data.

Conclusions:

• Visualizing social expectations can enhance data recall, particularly with high consensus.
• The alignment between personal, social, and data expectations significantly influences trust and interpretation.