Back to Search
Start Over
Visual Attention Quality Research for Social Media Applications: A Case Study on Photo Sharing Applications.
- Source :
-
International Journal of Human-Computer Interaction . Jul2024, Vol. 40 Issue 14, p3827-3840. 14p. - Publication Year :
- 2024
-
Abstract
- With the rapid growth of smart terminal industry and User-Generated Content products, Social Media Applications (SMA) products, represented by TikTok, have been booming growth. How to capture and maintain users' attention in order to prolong their stay on the product and increase customer stickiness has become the focus of the industry. Therefore, according to the duration and characteristics of users using SMA, this paper takes the layout of SMA as an example to study the visual attention quality. Firstly, through the literature review, the study of visual attention quality in SMA was summarized into four aspects, including the span, maintenance, allocation, and switch of attention. Secondly, eye movement and behavior experiments were designed based on common content consumption tasks of SMA users to verify the hypotheses proposed in this paper. According to the results: (1) In terms of attention maintenance, linear layout outperformed masonry layout, masonry layout outperformed matrix layout, and in terms of attention span, the reverse was true; (2) In attention allocation, linear layout showed the best anti-interference characteristics; The masonry layout is suitable to be used in the task search stage and also in the dual-task execution stage; (3) In terms of attention switch, the energy cost of attention switch increased in the order of matrix layout, masonry layout and linear layout. (4) In terms of interaction, double-clicking interaction had more advantages in attention allocation and cognitive load than swiping interaction. The research in this paper has provided objective and quantitative data support for the design and operation of SMA products. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 10447318
- Volume :
- 40
- Issue :
- 14
- Database :
- Academic Search Index
- Journal :
- International Journal of Human-Computer Interaction
- Publication Type :
- Academic Journal
- Accession number :
- 178419079
- Full Text :
- https://doi.org/10.1080/10447318.2023.2201556