Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: What Makes a Data-GIF Understandable?   GIFs are enjoying increasing popularity on social media as a format for
data-driven storytelling with visualization; simple visual messages are
embedded in short animations that usually last less than 15 seconds and are
played in automatic repetition. In this paper, we ask the question, "What makes
a data-GIF understandable?" While other storytelling formats such as data
videos, infographics, or data comics are relatively well studied, we have
little knowledge about the design factors and principles for "data-GIFs". To
close this gap, we provide results from semi-structured interviews and an
online study with a total of 118 participants investigating the impact of
design decisions on the understandability of data-GIFs. The study and our
consequent analysis are informed by a systematic review and structured design
space of 108 data-GIFs that we found online. Our results show the impact of
design dimensions from our design space such as animation encoding, context
preservation, or repetition on viewers' understanding of the GIF's core
message. The paper concludes with a list of suggestions for creating more
effective Data-GIFs.

24
The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
3
The categories of this paper are: physics
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
16
The categories of this paper are: stat