Emotion Alignment: Discovering the Gap Between Social Media and Real-World Sentiments in Persian Tweets and Images
This addresses the problem of emotional misalignment in social media for Persian communities, though it is incremental as it applies existing methods to new data.
The study measured the gap between real-world and social media emotions in Persian users, finding 28.67% similarity for images and 75.88% for tweets with real-world feelings.
In contemporary society, widespread social media usage is evident in people's daily lives. Nevertheless, disparities in emotional expressions between the real world and online platforms can manifest. We comprehensively analyzed Persian community on X to explore this phenomenon. An innovative pipeline was designed to measure the similarity between emotions in the real world compared to social media. Accordingly, recent tweets and images of participants were gathered and analyzed using Transformers-based text and image sentiment analysis modules. Each participant's friends also provided insights into the their real-world emotions. A distance criterion was used to compare real-world feelings with virtual experiences. Our study encompassed N=105 participants, 393 friends who contributed their perspectives, over 8,300 collected tweets, and 2,000 media images. Results indicated a 28.67% similarity between images and real-world emotions, while tweets exhibited a 75.88% alignment with real-world feelings. Additionally, the statistical significance confirmed that the observed disparities in sentiment proportions.