Abstract
Background/Objectives: The increasing use of social media for sharing health and diet experiences presents new opportunities for nutritional research and dietary assessment. Large language models (LLMs) and artificial intelligence (AI) offer innovative approaches to analyzing self-reported data from online communities. This study explores weight loss experiences associated with the ketogenic diet (KD) using user-generated content from Reddit, aiming to identify trends and potential biases in self-reported outcomes. Methods: A dataset of 35,079 Reddit posts related to KD was collected and processed. Posts mentioning weight loss, diet duration, and additional factors (age, gender, physical activity, health conditions) were identified, yielding 2416 complete cases. Descriptive statistics summarized weight loss distributions and diet adherence patterns, while linear regression models examined factors associated with weight loss. Results: The median reported weight loss was 10.9 kg (IQR: 4.4-22.7 kg). Diet adherence varied with 36.3% of users following KD for up to 30 days and 7.8% for more than a year. Metabolic (27%) and cardiovascular disorders (17%) were the most frequently reported health conditions. Adherence beyond one year was associated with an average weight loss of 28.2 kg (95% CI: 25.5-30.9) compared to up to 30 days. Male gender was associated with an additional weight loss of 5.2 kg (95% CI: 3.8-6.6) compared to females. Conclusions: Findings suggest KD may lead to substantial weight loss based on self-reported online data. This study highlights the value of social media data in nutritional research, uncovering hidden dietary patterns that could inform public health strategies and personalized nutrition plans.