Micro Data Videos (mDVs) are up to one-minute data-driven vertical video clips for mobile devices. Widely adopted on social media platforms, mDVs hold significant potential for disseminating information. Despite their growing prevalence, little is known about their components and how they are designed. Thus, two studies were conducted. Study 1 analyzed 40 mDVs and revealed their narrative components. Study 2 examined, through design sessions with design experts, how such components are assembled to craft storyboards for mDVs. The diverse narrative styles of mDVs render them flexible and suitable for multiple topics and purposes. Further, many include a “Linker" directing viewers to external online resources. Participants approached their design in a structural yet iterative manner with emphasis on setting up a “hook” in the opening seconds to capture attention. We summarize and share common design practices used in creating mDVs, an increasingly important medium in data storytelling.

Data Videos (DV) have been used in a diverse set of fields. However, the possibility of utilizing them with social robots for further improving the viewer’s engagement is yet to be examined. While social robots have been used in various presentation-related applications, there is also a lack of design instructions on how to better utilize them. Hence with this early work, we explore the possibility of using social robots as potential DV presenters through; a quantitative analysis of the factors of visible presenters in DVs, and a testing phase of these factors via four group design sessions involving experienced designers. From the DV analysis, we identified 12 unique techniques across four main factors. The observations from the group design sessions show that these findings overlap with the design practices of experienced designers when designing robotic presentations.

Research suggest negative feedback could guide users’ behaviours effectively in Human-AI interactions. However, providing negative feedback, relative to positive counterparts, can be more challenging in any type of communication. This paper delves into the potential of a social robot in delivering negative feedback for improving the in-class learning experience for children. With child participants (12 and younger), we conducted three co-design studies to investigate their preferred facial expressions of a social robot, Haru, which can identify them being distracted (i.e., undesirable behaviour), and redirect their attention back to their task with the facial expressions. Altogether, results indicated that children do not want to see conventional punishing expressions (e.g., angry faces) as a reaction to their undesirable behaviour. Instead, they preferred pleasant ones (e.g., funny, cute). Further, the importance of using realistic stimuli for studies and the co-design approach, as well as the challenges of interpreting children’s drawing responses, are discussed.

Tabletop social robots are becoming increasingly common, not only as social companions but as presenters and orators of information. We present an exploration of utilizing robots as a multimodal presentation tool to communicate data-driven facts. Our exploration is inspired by the wealth of research on data videos (DVs) as these have become mainstream sources for swiftly conveying data-driven information to a mass audience. We first analyze 48 DVs that contain visible narrators (presenters who are visible in the video frames) as our source for understanding the techniques used to convey factual information via presenters. Twelve dimensions across four factors (presenter-grounded; narrative-grounded; viewer-engagement-related; and data-visualization-related) were identified. These factors were carefully arranged in designing presenters to engage the audience with the video content. We adapt these findings to the design of an expressive social tabletop robot that can communicate data-driven knowledge to its audience. Supported by four design sessions with expert content creators and designers, we provide nine design implications for designing multimodal presentations with an expressive tabletop social robot. We conclude with the possible application potentials of this unique data presentation modality.

The current pandemic showed us the importance of swiftly disseminating data-based information to the masses of people. This study explores an affect-centered narrative to convey data-driven messages regarding contact tracing apps (CTAs) using video as a medium (i.e., data video). A between-subjects online study compared the effect of three storytelling approaches on viewers' perception. A video developed by Google was selected as the baseline video (Control Condition; 2min 23s) due to its high quality and relevance to CTAs. The central messages of this baseline video were; a) how CTAs work, and b) how safe and effective CTAs are. Infographics supporting these messages were then added to the baseline video (the second condition; 3min 19s); this was a simple data video (DV), and it did not intend to induce specific emotional experiences in participants (i.e., cognition-centered video). Finally, an affect-focused DV (AFDV) was also created by emphasizing the emotion-based narrative aspect of the message (the third condition; 4min 6s). In this video, three cute human-like cartoon characters were introduced. Viewers in this condition needed to process both cognitive and affective information. Note all three videos (i.e., control video, DV, and AFDV) conveyed identical messages. Participants watched one of these three videos only once, and we explored the video effect on their perception. Our results repeatedly indicated the potential benefits of including affect in data storytelling.

Data Videos (DVs), or animated infographics that tell stories with data, are becoming increasingly popular. Despite their potential to induce attitude change, little is explored about how to produce effective DVs. This paper describes two studies that explored factors linked to the potential of health DVs to improve viewers’ behavioural change intentions. We investigated: 1) how viewers’ affect is linked to their behavioural change intentions; 2) how these affect are linked to the viewers’ personality traits; 3) which attributes of DVs are linked to their persuasive potential. Results from both studies indicated that viewers’ negative affect lowered their behavioural change intentions. Individuals with higher neuroticism exhibited higher negative affect and were harder to convince. Finally, Study 2 proved that providing any solutions to the health problem, presented in the DV, made the viewers perceive the videos as more actionable while lowering their negative affect, and importantly, induced higher behavioural change intentions.