Study on the Optimization of Digital Content Reading Experience Based on Scene Theory

Abstract

In the Web 3.0 era, digital reading has become the main way to obtain information and information, and the scenario-based communication method has put forward higher requirements for product services. However, it is found that current digital reading applications still have problems such as information overload, inconvenient interaction, and easy to cause user reading fatigue. Therefore, in order to optimize users’ digital reading experience, this paper proposes a method to construct target scenes and design adaptive interfaces based on scene theory, taking existing digital reading applications as an example. Firstly, based on scene theory, we initially divide the scene, and then use EEG and focus groups to extract users’ visual, auditory and interactive action preferences for digital reading and build the target scene; secondly, based on emotional design, we refine the design strategy to better meet users’ reading needs for existing problems; finally, we design the scene mode according to the needs of the scene, and prove through questionnaire evaluation that this design strategy can reduce users’ cognitive.Finally, we design the scenario model according to the needs of the scenario, and prove through questionnaire evaluation that this design strategy can reduce users’ cognitive burden, relieve reading fatigue, and realize the unification of reading scenario and users’ perception. In order to test the scientificity and effectiveness of the design method, WeRead is chosen as a typical case study.