
Pictographic representations and animation techniques are commonly incorporated into narrative visualizations such as data videos. General belief is that these techniques may enhance the viewer experience, thus appealing to a broad audience and enticing the viewer to consume the entire video. However, no study has formally assessed the effect of these techniques on data insight communication and viewer engagement. In this paper, we first propose a scale-based questionnaire covering five factors of viewer engagement we identified from multiple application domains such as game design and marketing. We then validate this questionnaire through a crowdsourcing study on Amazon's Mechanical Turk to assess the effect of animation and pictographs in data videos. Our results reveal that each technique has an effect on viewer engagement, impacting different factors. In addition, insights from these studies lead to design considerations for authoring engaging data videos.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 55 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
