Towards Modelling Language Innovation Acceptance in Online Social Networks

Language change and innovation is constant in online and offline communication, and has led to new words entering people’s lexicon and even entering modern day dictionaries, with recent additions of ‘e-cig’ and ‘vape’. However the manual work required to identify these ‘innovations’ is both time consuming and subjective. In this work we demonstrate how such innovations in language can be identified across two different OSN’s (Online Social Networks) through the operationalisation of known language acceptance models that incorporate relatively simple statistical tests. From grounding our work in language theory, we identified three statistical tests that can be applied - variation in; frequency, form and meaning. Each show different success rates across the two networks (Geo-bound Twitter sample and a sample of Reddit). These tests were also applied to different community levels within the two networks allowing for different innovations to be identified across di�...

• Type: Journal
• Year: 2016
• Where: WSDM
• Authors: Daniel Kershaw, Matthew Rowe, Patrick Stacey
• Keywords: Data Mining, WSDM 2016