Effects of title wording on memory of trends in line graphs
Résumé
Graphs and data visualizations can give us a visual sense of trends on topics ranging from poverty, the spread of diseases, the popularity of products, etc. What makes graphs useful is our ability to perceive these trends at-a-glance. Related work has investigated the effect of different properties of graphs, including axis scaling, the choice of encoding, and the presence of pictographic elements (e.g., Haroz et al. 2015) on the perception of trends or remembered size of the quantities depicted. Previous work has shown that visual attention is directed towards the text and specifically titles, which can affect what is recalled from memory (Borkin, Bylinskii, et al. 2016; Matzen et al. 2017). In a more controlled setting, we investigate how wording in a line graph's title impacts memory of the trend's slope. We designed a set of experiments that consist of first showing participants a simple graph with an increasing or decreasing trend, paired with a title that is either strongly stated ("Contraceptive use in Senegal skyrockets") or more neutral ("Contraceptive use in Senegal rises"). To avoid rehearsal, participants then performed a challenging task, before being asked to recall the title and answer a question about the graph's initial/final value or an extrapolated value. Can we change a participant's memory of a graph by modifying some accompanying text? These experiments bear resemblance to the eyewitness testimony experiments by Loftus et al. (1996). In some conditions, the strength of the wording in the title affects how participants recall the trend from memory, but this effect is not universal across experiments. Results of these experiments have important implications for how text interacts with long term visual memory and may bias future inferences.
References
Haroz, S., Kosara, R., & Franconeri, S. L. (2015). Isotype visualization: Working memory, performance, and engagement with pictographs. In Proceedings of the 33rd annual ACM conference on human factors in computing systems. DOI: https://doi.org/10.1145/2702123.2702275
Borkin, M. A., Bylinskii, Z., Kim, N. W., Bainbridge, C. M., Yeh, C. S., Borkin, D., ... & Oliva, A. (2016). Beyond memorability: Visualization recognition and recall. IEEE transactions on visualization and computer graphics, 22(1), 519-528.