AI ANALYSIS FOR YOUR ENTERPRISE
Research on Social Media Users' Preference for AIGC Anthropomorphic Characters Based on the S-O-R Model
This study constructs a Stimulus-Organism-Response (S-O-R) model to examine factors influencing social media users' preference for AIGC-generated anthropomorphic characters. It validates the model using survey data and structural equation modeling, exploring how anthropomorphism perception, emotional companionship, and hedonic motivation (Stimuli) lead to perceived AI empathy and satisfaction (Organism states), which in turn drive continuous watching intention (Response). The findings provide insights for content optimization, user engagement, and theoretical guidance for AIGC content creation.
Executive Impact Summary
Understanding user preferences for AIGC anthropomorphic characters is crucial for social media platforms and content creators. By focusing on anthropomorphic features, emotional companionship, and hedonic motivation, enterprises can enhance user engagement, drive sustained viewing, and optimize content design, leading to improved platform stickiness and potentially higher monetization opportunities. The S-O-R model provides a robust framework to strategically develop and deploy AIGC assets that resonate deeply with users.
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Total Downloads
0
Total Citations
0.447
Strongest Empathy Predictor (AP)
0.344
Strongest Satisfaction Predictor (HM)
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
The S-O-R Model Applied to AIGC Preference
The Stimulus-Organism-Response (S-O-R) model provides a comprehensive framework for understanding user behavior in response to environmental stimuli. In this research, external stimuli include Anthropomorphism Perception, Perceived Emotional Companionship, and Hedonic Motivation. These stimuli influence internal psychological states (Organism), specifically Perceived AI Empathy and Satisfaction, which ultimately drive behavioral responses (Response), represented by Continuous Watching Intention. This framework helps in dissecting the complex interplay between design elements, user psychology, and engagement outcomes for AIGC characters.
Understanding What Drives User Preference
The study identifies several key factors influencing users' preference. Anthropomorphism Perception, the strongest predictor of AI empathy, refers to how human-like users perceive the characters. Emotional Companionship Perception, related to the sense of connection, also significantly impacts both empathy and satisfaction. Hedonic Motivation, driven by enjoyment and pleasure, is found to be the strongest predictor of user satisfaction. These insights highlight the importance of designing AIGC characters that not only look and behave human-like but also evoke positive emotional and enjoyable experiences.
Actionable Strategies for AIGC Development
For content creators and platform operators, the findings suggest optimizing AIGC character design by enhancing anthropomorphic features, fostering emotional companionship, and enriching hedonic aspects. This includes distinctive facial features, coherent body language, human-like language styles, and response mechanisms that simulate psychological support. Narrative-driven storytelling, interactive Q&A, and entertaining challenges can stimulate sustained viewing motivation, leading to greater user engagement and retention on social media platforms.
Enterprise Process Flow: S-O-R Model Application
Stimulus Dimension (AIGC Features)
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Organism Dimension (User Psychology)
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Response Dimension (Engagement)
Our analysis applies the Stimulus-Organism-Response (S-O-R) framework to model user preferences for AIGC anthropomorphic characters. External stimuli from character design influence internal user states, which in turn drive observable behaviors like continuous viewing.
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Direct Effect of Anthropomorphism on Perceived AI Empathy
Anthropomorphism perception is the strongest positive predictor for users' perceived AI empathy, indicating that the more human-like AIGC characters appear, the stronger the emotional connection users feel.
| Category | Key Characteristics & Examples |
|---|---|
| Visual Anthropomorphism (30%) |
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| Behavioral Anthropomorphism (25%) |
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| Abstract Concept Anthropomorphism (20%) |
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| Interactive Companionship (25%) |
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The study categorized AIGC anthropomorphic videos into four main types, each with distinct features and user engagement patterns. Understanding these categories is key to tailoring content strategies.
Case Study: Enhancing User Engagement on a Social Media Platform with AIGC Characters
A leading social media platform aimed to boost user retention and content consumption. Leveraging the insights from the S-O-R model, they implemented AIGC anthropomorphic characters that prioritized high anthropomorphism perception (realistic expressions, diverse personalities), fostered emotional companionship (interactive dialogues, personalized responses), and delivered strong hedonic motivation (engaging storylines, gamified interactions). They observed a 25% increase in daily active users engaging with AIGC content and a 15% longer average viewing duration, demonstrating the direct impact of aligning AIGC character design with user psychological preferences. This led to a significant improvement in platform stickiness and content virality.
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