ONLINE SHOPPING USER PORTRAIT MODEL CONSIDERING PSYCHOLOGICAL AND EMOTIONAL FACTORS
Authors: Xu Yong , Wang Qian , Roxas Rachel Edita O , Sun Yutao , Li Xiaoyu , Lv Xizhi 
Published: July 2022

Background

With the emergence of Web 3.0 era, more and more enterprises begin to pay attention to the research of “personalization”. Personalized recommendation is not only through the simple classification of users' basic attributes, but also through the collection of various content data generated by users on the network, in-depth analysis of text, statistics of user behavior and other methods to find hidden user interests, so as to provide personalized services more accurately. As a data analysis tool, user portrait model can better obtain the effective information of users and describe the characteristics of user groups. It is widely used in personalized recommendation, precision marketing, behavior prediction, anomaly detection and other fields to improve service efficiency and user satisfaction.

Research Objects and Methods

Analyze and quantify the emotion of the comment text in detail. After extracting the main aspects of users' attention to the product, the real emotion expressed by users who buy the product is calculated, and a user portrait model with multi-attribute features is proposed. This paper constructs a multi-dimensional user portrait index system from four aspects: user basic attributes, interaction attributes, feedback attributes, psychological and emotional attributes and situational attributes. Secondly, based on entropy theory, the overall interaction value a is calculated according to the interaction index value; Then, the user evaluation SC and user comment emotion se are taken as the indicators of user feedback attributes. Then, TF-IDF method is used to distinguish the important features of users' psychological interest, and the feature weight of interaction index is obtained to show the differences between users. Finally, a portrait model considering emotional factors is established. In order to verify the impact of user portrait model on customer emotion, this study uses relevant women (half and half) to participate in this study. The experimental design, screening method, dependent variable index and experimental method are the same as above. Examples of receiving instructions are as follows: the red circle will prompt, and then there will be negative emotional stimulation. Even if it makes me feel unhappy, it is normal. I should fully accept the unpleasant feeling and let my feeling flow naturally without controlling it. The guidelines for avoidance are as follows: the red circle will prompt, and then there will be negative emotional stimulation. Although I don't know what the specific content is, I should try my best to avoid this stimulation and avoid this negative emotional feeling. A series of experiments were conducted to explore how different cognitive styles of healthy individuals affect the emotional effects caused by expectation and the regulation of expectation on the emotional arousal of subsequent stimuli. Study 4.3 intends to further investigate whether and how adaptive cognitive style training can change the excessive negative expectations of anxiety patients (taking high trait anxiety as an example), so as to intervene in clinical anxiety symptoms. This study intends to screen and recruit 180 subjects with high trait anxiety from college students (90 men and 90 women). According to previous studies, it is planned to measure the State Trait Anxiety Questionnaire (measuring the level of state anxiety and trait anxiety) and the positive emotion Negative Emotion Scale (measuring mood state) among college students. Subjects with more than 85% of the normal distribution of trait anxiety scores were regarded as subjects with high trait anxiety. The above subjects were randomly divided into four groups: separate reappraisal training group, active reappraisal training group, training group and their respective control group (30 in each group, half male and half female). Before starting the cognitive style training program, the negative expectations and emotional effects of the subjects in the experimental group and the control group (taking behavior, skin electricity and EEG as indicators) were pretested. The negative expected intensity was measured by uncertain cue.

Results

The subjects in the experimental group then received cognitive style training, and the subjects in the control group received control training for 3 months. After the training, the four groups of subjects were measured again for state trait anxiety, negative expected intensity and positive effect scale. Through the comparison between the experimental group and the control group, finally comprehensively evaluate the intervention effect of cognitive style training on excessive negative expectation and trait anxiety symptoms.

Conclusions

The model can describe the interests and preferences of different user groups more carefully and accurately, and provide effective support for personalized services. In short, we should integrate relevant designs according to our own advantages and characteristics. With the goal of excellent brand design examples, regularly hold successful model sharing, experience introduction, project display and other activities, establish successful brand examples for building customers' positive emotions, clarify the specific objectives of the activities, give full play to the concentration of professionals, high IQ and professional knowledge in the commercial field, give full play to the advantages of talents and intelligence, and organize experts and scholars to form a professional bid winning guidance team, Give full play to the role of professional experts and scholars in commercial projects in this field and carry out scientific research on relevant projects.

Acknowledgments

This work was supported by Philosophy and Social Science Planning project of Anhui Province under Grant No. AHSKF2021D31.