对比波斯语推文与真实情绪，发现文字更贴近现实，图像则差异显著。
Emotion Alignment: Discovering the Gap Between Social Media and Real-World Sentiments in Persian Tweets and Images
- 用双模态分析框架比较社交媒体与真实情绪
- 推文与真实情绪匹配度达75.88%，图像仅28.67%
- 揭示社交表达中的情绪失真现象，适合情感计算研究者参考
在当代社会，社交媒体广泛融入日常生活。然而，现实世界与线上平台间的情绪表达可能存在差异。本研究以X平台上的波斯语用户群体为对象，全面探究该现象。设计了一套创新分析流程，通过基于Transformer的文本与图像情感分析模块，对参与者近期推文和图像进行分析，并收集其亲友对真实情绪的反馈，采用距离准则对比虚拟体验与真实感受。研究共纳入105名参与者、393位提供视角的朋友，收集超8,300条推文及2,000张媒体图像。结果显示，图像与真实情绪相似度为28.67%，而推文与真实情绪匹配度达75.88%。统计检验确认了情绪分布差异具有显著性。
原文摘要 · Abstract (English)
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.
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