The global adoption of electric vehicles (EVs) is critical for achieving sustainability and reducing carbon emissions. This study investigates how emotional expressions and post types in organization-generated content (OGC) influence public sentiment toward EVs, using data collected from Facebook. By employing sentiment analysis and linear regression models, the research evaluates the effects of positive and negative emotions, post types (photos, videos, others), reading complexity and control variables such as administrative country type. The results reveal that positive emotions like joy and trust significantly enhance public sentiment, while negative emotions, particularly fear, reduce it. Posts featuring photos outperform videos and other formats in driving favorable sentiment. Reading complexity negatively impacts sentiment, emphasizing the need for clear and accessible language. Additionally, posts from non-developed countries exhibit lower sentiment scores compared to those from developed countries. These findings highlight the importance of crafting emotionally resonant and visually engaging content to promote EV adoption. The study offers actionable insights for organizations to optimize their communication strategies, fostering positive public perceptions and supporting the global transition to sustainable transportation. Future research could explore platform-specific effects and integrate user-generated content for a broader understanding of EV-related sentiment.