Conference Paper

#52 

@inproceedings{Zhao2019, title={Understanding Partitioning and Sequence in Data-Driven Storytelling: The Case for Comic Strip Narration.}, author={Zhenpeng Zhao and Rachael Marr and Jason Shaffer and Niklas Elmqvist}, url={http://users.umiacs.umd.edu/~elm/projects/datacomics/datacomics.pdf}, year={2019}, date={2019-04-01}, journal={Proceedings of the iConference}, booktitle={Proceedings of the iConference}, volume={11420}, pages={327--338}, publisher={Springer}, abstract={The comic strip narrative style is an effective method for data-driven storytelling. However, surely it is not enough to just add some speech bubbles and clipart to your PowerPoint slideshow to turn it into a data comic? In this paper, we investigate aspects of partitioning and sequence as fundamental mechanisms for comic strip narration: chunking complex visuals into manageable pieces, and organizing them into a meaningful order, respectively. We do this by presenting results from a qualitative study designed to elicit differences in participant behavior when solving questions using a complex infographic compared to when the same visuals are organized into a data comic.}, keywords={}, }