Storytelling in data visualization: information bias

Abstract

Storytelling is shown as an effective approach to humanize information perception. However, its potential to build a biased view of the information contents is often neglected. Moreover, narrative understanding and emotion may interfere with data visualization comprehension. In this research, we evaluated how users perceived the information in two different configurations: One with a report with graphs and narrative side notes texts, and the second with a redesigned fully annotated content. The test compared the two groups in both qualitative and quantitative methods. The quantitative results were obtained by a survey and statistically analyzed with a T-Test. This indicated that the condescending storytelling approach augmented the perception of the effect signaled by the presented narrative. Also, the qualitative results collected afterward by interview and focus group have shown that, as the readers of narrative models perceived a higher intensity of the effect, they have also expected an even higher result from the selected data. The final analysis of the experiment helped to indicate that ordering, highlights, and semantics have a strong role in how the narrative influences the perception of the reader.