From Adoption to Adaption: Tracing the Diffusion of New Emojis on
  Twitter
Yuhang Zhou Xuan Lu Wei Ai
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.