Yajuan Zhu's research while affiliated with Chongqing Technology and Business University and other places

This paper analyzes the network expression and audience participatory discourse system under the mainstream media communication mode, combines the audiovisual multimodal audience cognitive participation and the multimodal features of the mainstream media, and proposes a multimodal deep learning model based on mainstream media communication. Based on the picture vision and human emotion migration methods, the picture vision feature migration module and the text emotion migration module are constructed respectively, and the multimodal feature fusion model is built by applying the gradient enhancement decision tree. Linguistic modality analysis of mainstream media communication discourse is carried out by analyzing the development characteristics of audience participatory cultural communication modes. The influence of different mainstream media communication discourses on the audience’s participatory culture is examined through logistic regression analysis while screening network discourse access. The regression analysis shows that the mainstream media communication modes represented by social software and microblogging have a significant impact on the development of the audience’s participatory culture, with p-values of 0.0452 and 0.0068, respectively, and thus the mainstream media need to strengthen content innovation, focus on specific audience groups, and make full use of new media platforms to provide audiences with richer, more accurate and professional news services.

Background Brand image design starts with sensory stimulation. Consumers experience the brand image, recognize the brand, and purchase goods through their senses, which is a comprehensive experience. Eliminating psychological barriers requires starting from an emotional perspective, as brand emotionalization often occurs from the beginning of user contact, and is conveyed through the senses to establish a “sensory” level emotional experience. This study utilizes cognitive psychology to analyze consumers’ bidirectional emotional barriers and establish a positive and emotional brand image. Subjects and Methods This study uses SWOT analysis and semantic difference analysis methods. In terms of graphics, colors, and fonts proposed by a certain brand, eye tracking experiments will be conducted to collect images. 10 samples that meet the standards will be selected for redesign, and 4 of them will be evaluated through a questionnaire survey. SPSS23.0 statistical software will be used for statistical analysis to compare the significant differences in the results, and select the design scheme that best meets the emotional needs of consumers with bipolar disorder. Results This brand image design based on cognitive psychology has analyzed the emotional characteristics and aesthetic experience of depressed consumers, and the sensory needs of patients with bipolar disorder are more moderate and smooth sensory elements. Conclusions This study utilizes a multi-sensory participation in brand image design and sensory interaction design mechanism, focusing on consumers themselves, allowing bipolar disorder groups to fully experience brand information and create a pleasant experience, and integrate into society. Acknowledgement General research projects of Pass College of Chongqing Technology and Business University in 2020 (No. KY202010).