From linguistic innovation in blogs to language learning in adults : what do interaction networks tell us?

Abstract

Social networks have been found to play an increasing role in human behaviour and even the attainment of individuals. We present the results of two projects applying SNA to language phenomena. One involves exploring the social propagation of ne ologisms in a social software (microblogging service), the other investigating the impact of social network structure and peer interaction dynamics on second-language learning outcomes in the setting of naturally occurring face-to-face interaction. From local, low-level interactions between agents verbally communicating with one another we aim to describe the processes underlying the emergence of more global systemic order and dynamics, using the latest methods of complexity science. In the former study, we demonstrate 1) the emergence of a linguistic norm, 2) that the general lexical innovativeness of Internet users scales not like a power law, but a unimodal, 3) that the exposure thresholds necessary for a user to adopt new lexemes from his/her neighbours concentrate at low values, suggesting that—at least in low-stakes scenarios—people are more susceptible to social influence than may erstwhile have been expected, and 4) that, contrary to common expectations, the most popular tags are characterised by high adoption thresholds. In the latter, we find 1) that the best predictor of performance is reciprocal interactions between individuals in the language being acquired, 2) that outgoing interactions in the acquired language are a better predictor than incoming interactions, and 3) not surprisingly, a clear negative relationship between performance and the intensity of interactions with same-native-language speakers. We also compare models where social interactions are weighted by homophily with those that treat them as orthogonal to each other