Semantic Journeys: Quantifying Change in Emoji Meaning from 2012-2018
This work addresses the dynamic nature of emoji meaning for researchers in computational linguistics and social media analysis, offering a novel dataset and insights into semantic evolution.
The authors conducted the first longitudinal study of emoji semantics over six years of Twitter data, identifying five patterns of semantic change and finding that less abstract emoji are more likely to change meaning.
The semantics of emoji has, to date, been considered from a static perspective. We offer the first longitudinal study of how emoji semantics changes over time, applying techniques from computational linguistics to six years of Twitter data. We identify five patterns in emoji semantic development and find evidence that the less abstract an emoji is, the more likely it is to undergo semantic change. In addition, we analyse select emoji in more detail, examining the effect of seasonality and world events on emoji semantics. To aid future work on emoji and semantics, we make our data publicly available along with a web-based interface that anyone can use to explore semantic change in emoji.