Restructuring Dietary Behaviors in the Digital Intelligence Environments: Social Media, Artificial Intelligence, and Health-Conscious Food Choices

The deep integration of digital and intelligent technologies is systematically reconfiguring the cognitive decision-making framework of human dietary behavior. Social media communication mechanism is significantly influencing people's dietary behavior. In recent years, the global phenomenon of “cell phones eat first” has prompted food and beverage brands to proactively utilize social media to attract customers through “aesthetically pleasing food” visual marketing. Concurrently, advancements in artificial intelligence (AI), particularly in personalized recommendation systems based on reinforcement learning models, are intensifying these effects. These systems continuously optimize the delivery of highly appealing and, sometimes, addictive foods through multimodal content and customized dietary plans, potentially exacerbating the risk of imbalanced nutritional intake.

This Research Topic focuses on interdisciplinary research at the intersection of digital-intelligent environments and dietary behaviors, with three primary objectives:

Mechanistic Exploration: Through integrating theories from communication studies, computational nutrition science, and behavioral sciences, we aim to collect studies that systematically investigate the hierarchical impact pathways of social media interaction cues (e.g., emotional reinforcement mechanism of likes/comments), AI-driven information dissemination features (including nutritional knowledge generation bias of large language models and addictive design patterns of algorithmic recommender systems).

Ecological Construction: We seek to develop a comprehensive regulation model that includes algorithmic strategies (personalized delivery of healthy and nutritious food), digital health literacy (critical processing of information), and neuroadaptive assessment (dynamic balance between the dopamine reward system and nutritional needs), to promote the sustainable adaptation of healthy diets through technology.

Applied Evaluation: We aim to incorporate both empirical and evidence-synthesis research—including randomized controlled trials, pilot studies, longitudinal designs, and systematic reviews—that assess the effectiveness of digital twins, recommender systems, and mobile health applications in improving individuals’ overall health status. This objective ensures that theoretical insights and regulatory models are grounded in rigorous, real-world evidence.

We welcome submissions, including but not limited to the following subtopics:

● Association between social media interaction cues (e.g., affective reinforcement mechanisms embedded in likes/comments) and food rewards, obesity, and nutrition decision-making behaviors
● The impact of AI-driven information propagation (including nutritional knowledge biases generated by large language models and addictive design patterns in algorithmic recommendation systems) on food processing, obesity, and nutritional decision-making processes.
● Social media-based interventions for nutritional food decision-making.
● Interventions based on AI algorithmic strategies for nutritional food decision making.
● Digital health literacy enhancement (critical information processing competencies).
● Neural mechanisms of food processing driven by digital-intelligent environments, for example exploring the influence of social media visual stimuli and AI personalized recommendations on neural circuits on the prefrontal-limbic system and establishing neural plasticity-behavioral modification-environmental adaptations based on neurofeedback training procedures.
● Empirical studies, including randomized controlled trials, pilot interventions, and longitudinal research, evaluating digital twins, recommender systems, or mobile health applications.
● Systematic reviews and meta-analyses synthesizing evidence on digital technologies for dietary or broader health improvement.

Keywords: Artificial Intelligence, Social Media, Health-Conscious food choices, obesity

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.