Static or Dynamic: An experimental study : The Impact of animation principles on user engagement on LinkedIn

Abstract: Engagement. This has become a key concept in the field of marketing. The concept of "engagement" is utilized to describe the way users instantly engage with brands using clicks, reactions, comments, and sharing. Brands and advertisers utilize media platforms to increase brand awareness and create customer-engaging content. In recent years, most platforms have utilized motion graphics and animations to produce more dynamic content, separate themselves from competitors, and create engaging content. Nevertheless, is it possible to increase engagement by using animation principles? The objective of this research is to gain an understanding of how the principles of animation can be used to improve engagement on LinkedIn, as well as the impact these principles may have on social networking site platforms, and to determine which types of content are the most engaging. The following research question was asked: RQ1: How does the use of animation principles in dynamic posts influence the level of engagement on LinkedIn compared to static posts? In this study, an inductive and empirical approach through the Visual Attention Theory was used. A quantitative content analysis was performed on the companies' LinkedIn profiles to gather data on engagement. The content analysis was performed on LinkedIn in a real-world scenario using Ny Studio, Grace Studio, and Saga Production’s accounts. In total, 18 posts—three static and three dynamic were uploaded on each of the company's LinkedIn accounts. The collected data was inserted into the engagement metric to be further analyzed. Compared to static posts on LinkedIn, the dynamic post with the principles of animation did not yield significantly higher engagement. The animation of principles does, however, affect a post's comments, reactions, and shares. At the same time, static posts showed higher engagement in terms of views and clicks. The independent t-test resulted in a significant (p < 0.001) value for the engagement metric of clicks. This reveals that static post engagement on clicks does differ substantially in this study compared to dynamic posts. The findings contribute to the limited understanding of how dynamic LinkedIn affects user engagement and have laid the groundwork for further research in this area.