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. 2023 Nov 20;13(1):20291.
doi: 10.1038/s41598-023-47120-w.

Statistical characteristics of comic panel viewing times

Hikaru Ikuta  1 , Leslie Wöhler  2 , Kiyoharu Aizawa  3
Affiliations

Statistical characteristics of comic panel viewing times

Hikaru Ikuta et al. Sci Rep. .

Abstract

Comics are a bimodal form of art involving a mixture of text and images. Since comics require a combination of various cognitive processes to comprehend their contents, the analysis of human comic reading behavior sheds light on how humans process such bimodal forms of media. In this paper, we particularly focus on the viewing times of each comic panel as a quantitative measure of attention, and analyze the statistical characteristics of the distributions of comic panel viewing times. We create a user interface that presents comics in a panel-wise manner, and measure the viewing times of each panel through a user study experiment. We collected data from 18 participants reading 7 comic book volumes resulting in over 99,000 viewing time data points, which will be released publicly. The results show that the average viewing times are proportional to the text length contained in the panel's speech bubbles, with a rate of proportion differing for each reader, despite the bimodal setting. Additionally, we find that the viewing time for all users follows a common heavy-tailed distribution.

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Conflict of interest statement

H.I. has received stipends partially based on a collaborative research project funded by BOOK WALKER Co., Ltd. (Tokyo, Japan). L.W. and K.A. declares no competing interests.

Figures

Figure 1
Figure 1
(a) Panels are cropped for being shown in the user interface. The dotted lines indicate the region presented to the reader in the panel-wise comic viewing interface used in the user study experiment. (b) Panels are navigated using the arrow keys on the keyboard. The comic panels in the figure are referenced from the comic Saisoku!! Vol. 1 by Naomasa Matsuda, included as a part of the Manga109 dataset,. The comic panels are used under the permission of the author Naomasa Matsuda. Please see https://www.manga109.org/ for more details.
Figure 2
Figure 2
A box plot showing an overview of the entire dataset.
Figure 3
Figure 3
The relation between the panel’s speech bubble text length and the mean viewing times. For each data point, the mean is taken over the panels having the same text length. The error bars show the standard error. The mean viewing time has a strong correlation with the text length.
Figure 4
Figure 4
A scatter plot of the panel’s speech bubble text length and the entire viewing time data. The dots show the reading time of each panel, and the line shows the linear regression result.
Figure 5
Figure 5
The density functions of the viewing time distributions for each participant, with speech bubble text lengths of 0 to 10, 20 to 30, and 40 to 50 characters. The tail of the distributions are approximately linear in a log-log plot, showing the characteristics of a heavy-tailed distribution.
See this image and copyright information in PMC

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