The Influence of Danmaku Quantity on Video Time Estimation An Eye-Tracking Study on Cognitive Load and Moderating Factors

Danmaku interaction, an innovative method of engaging with online videos, has rapidly gained popularity. However, research on how danmaku (user-generated comments overlaid on videos) affects cognitive processes, such as attention and time perception, remains limited. This study investigated how the quantity of danmaku, as a factor of intrinsic cognitive load, influences the accuracy of video time estimation. Additionally, within the framework of cognitive load theory, this study explored how flow and addiction levels moderate the effect of effective cognitive load, as measured by actual fixations on danmaku, on time estimation. Findings show that an increase in danmaku quantity decreases the accuracy of time estimation, particularly in high-density danmaku videos, likely due to elevated intrinsic cognitive load. Moreover, flow and addiction levels were identified as key moderators, amplifying or dampening the relationship between effective cognitive load and time estimation. Utilizing eye-tracking technology, we uncovered the mechanisms underlying time estimation in danmaku videos, providing empirical evidence of how danmaku affects attention allocation, time perception, and cognitive load. These results have practical implications for video platform design, content creation, and advertising strategies, contributing to the development of a healthier online environment. Future research could expand on these findings by examining a broader range of video types and contexts to further understand the influence of intrinsic cognitive load on time estimation.