The frequent introduction of new emojis in each Unicode release creates a dynamic shift in social media content, providing a unique opportunity to explore the evolution of digital language. Analyzing a large dataset of sampled English tweets, we examine how newly released emojis gain popularity and evolve in meaning. We find that the community size of early adopters and emoji semantics are positively correlated with 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 the interpretation of new emojis. The framework demonstrates its effectiveness in improving downstream text 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.