A Computer Mediated Analysis of Neologisms Used by Turkish Speakers on X Social Media Platform

Abstract

Neologism refers to newly emerged words and expressions or new definitions for existing words or expressions. Neologisms are an essential part of lexicography and etymology studies since new words constantly emerge in lexicons due to the dynamic nature of languages. There are recent efforts to compile neologisms in Turkish for lexicology studies. In addition, social media application programming interfaces (APIs) have become a recent trend in compiling massive quantities of data. This study facilitates X API to gather Tweets from X to compile a corpus and analyse and categorise neologisms used on social media. The corpus is compiled from Tweets sent from Turkey in Turkish between 01.01.2023 and 31.12.203. The corpus amounts to 327.262 Tweets with a total word count of 2.463.075. These Tweets are then tokenised by using TRNLP for further analysis. The tokenised entries are morphologically analysed via TrMorph to account for lemmatisation. The resulting data was analysed to identify Turkish neologisms most prevalent on the social media platform X. The selected neologisms account for lemmatisation and semantic shifting. Definitions of all neologisms found in the study are explained with examples. These neologisms are then analysed based on five categories: their frequency in the data set, function, coinage, formation process, and source. The study finds that neologisms used by Turkish speakers on social media are primarily expressive in function. Furthermore, the study finds that all the neologisms formed through borrowings were directly taken from English. The study also presents five new neologism formation methods for the Turkish language: blending, hypocoristic neologisms, hybrid neologisms, phono-semantic shifts, and phraseology. Hypocoristic neologisms are proposed as a new neology formation method unique to Turkish.