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The language for expressing comparisons is often complex and nuanced, makingsupporting natural language-based visual comparison a non-trivial task. Tobetter understand how people reason about comparisons in natural language, weexplore a design space of utterances for comparing data entities. We identifieddifferent parameters of comparison utterances that indicate what is beingcompared (i.e., data variables and attributes) as well as how these parametersare specified (i.e., explicitly or implicitly). We conducted a user study withsixteen data visualization experts and non-experts to investigate how theydesigned visualizations for comparisons in our design space. Based on the richset of visualization techniques observed, we extracted key design features fromthe visualizations and synthesized them into a subset of sixteen representativevisualization designs. We then conducted a follow-up study to validate userpreferences for the sixteen representative visualizations corresponding toutterances in our design space. Findings from these studies suggest guidelinesand future directions for designing natural language interfaces andrecommendation tools to better support natural language comparisons in visualanalytics.

Comparison Conundrum and the Chamber of Visualizations: An Exploration of How Language Influences Visual Design