In the rapidly evolving landscape of social media, the introduction of new
emojis in Unicode release versions presents a structured opportunity to explore
digital language evolution. Analyzing a large dataset of sampled English
tweets, we examine how newly released emojis gain traction and evolve in
meaning. We find that community size of early adopters and emoji semantics are
crucial in determining their popularity. Certain emojis experienced notable
shifts in the meanings and sentiment associations during the diffusion process.
Additionally, we propose a novel framework utilizing language models to extract
words and pre-existing emojis with semantically similar contexts, which
enhances interpretation of new emojis. The framework demonstrates its
effectiveness in improving sentiment classification performance by substituting
unknown new emojis with familiar ones. This study offers a new perspective in
understanding how new language units are adopted, adapted, and integrated into
the fabric of online communication.

通过对采样的英语推特的大数据集进行分析，我们研究了新发布的表情符号在社交媒体中如何获得关注并发展其意义，发现早期采纳者的社群规模和表情符号的语义对其受欢迎程度至关重要，某些表情符号在传播过程中经历了意义和情感关联的显著转变，此外，我们提出一个使用语言模型提取具有语义相似背景的单词和已存在的表情符号的新框架，通过将未知新表情符号替换为熟悉的表情符号，该框架在情感分类性能方面展示了其有效性。本研究为理解新语言单位如何被采纳、改编和融入在线交流的过程提供了一个新的视角。