Detecting emerging vocabulary in a large corpus of Italian tweets

This exploratory study investigates lexical change and innovation in contemporary Italian micro-blogging using a corpus of 5.32 million timestamped and geotagged tweets sampled from the 2022 Italian Twitter timeline. We develop a new method to identify 720 unattested forms (347 forms and 373 hashtags) as candidate neologisms. Our results show that orthographic variation, univerbation, suffixation, loanwords and portmanteaus are the most common categories of lexical creation in the data analysed, which appears to be driven by creativity, amusement and attention-seeking behaviour rather than a need for new words to define new objects, events or situations.