Language innovation and change in on-line social networks

Language is fundamental to human communication, though throughout the course of history language has constantly evolved. This can currently be seen in the changing forms of colloquial language in various on-line social networks (OSN's). These innovations in language are even making it into every day life with the recent inclusion of `lol' and `ro' into modern dictionaries. Changes and varying forms of language pose challenges to both academics and people in business when attempting to asses and communicate with different communities. In this Ph.D, we aim to forecast online language change through the use of predictive and descriptive methodologies. Through using data sets mined from a number of OSNs, we aim to develop generalizable models and theories for assessing and predicting such language changes. We frame this work in structuration theory will allow for a structured analysis of the agent (user), the social structure and the dynamics between them. We draw on state of the art work and methods, including the development of neural nets to analysis language use and network and community classification to uncover social structures. Preliminary results have identified statistically significant innovations usage across communities across a number of OSN's, this was done though operationlizing known linguistic models of innovation acceptance.