Memetic Phrase Evolution: A Corpus Based Computational Analysis of Viral Language on Social Media

Abstract

Nowadays, language is a dynamic, developing system, with words and phrases gaining new meanings, with meanings changing, and even coming and going in a few weeks with the advent of social media. This research deals with evolutionary phonetics via computational approach based on a corpus. It analyzes a huge amount of data from websites like Twitter, YouTube, Reddit and other social media platforms, and gives insights into what makes a phrase go viral and how these phrases develop over time in terms of virality. Using techniques of frequency analysis, collocation patterns, sentiment tracking and temporal modeling, the work shows that memetic phrases undergo an evolutionary process much like that of biological evolution. The evolution of a meme is shown to be affected by the affordances of the platform, the ways people interact with the meme, and by contextual reinterpretations. A replication of a computational framework to investigate language change in online contexts is not only an independent contribution to the fields of corpus linguistics and digital discourse, but it may also serve as an example for other researchers interested in studying language change in digital settings.The terms used in the title are memetic phrases, viral language, social media discourse, corpus linguistics, computational linguistics, natural language processing, semantic shift, memetic drift, sentiment analysis, collocation analysis, temporal modeling, language evolution, digital discourse, lexical innovation, cross-platform analysis.