The usage-based account of language is the central approach of cognitive sociolinguistics and it emphasizes the effect of interactive language use in social networks on both language system and language variation. However, usage-based accounts of language should be more than a linear relationship between usage-based effects and language system. Social interactions give rise to fluctuations in frequency of usage, at the same time, individuals also form evaluations of their experiences in such interactions. This is a force that cannot be ignored. It could override usage-based accounts when a language feature is desired. However, to what extent such personal motivation can override is left for future exploration.
This study addresses the social-cognitive interactions that occur in code-switching and integrates social and cognitive factors from a usage-based perspective. It investigates code-switching in different interaction modes—speech and writing—to consider not only the influence from social factors (social networks and attitudes) but also the relative cognitive processing load. The data were gathered from 40 Chinese-English bilinguals in London, derived from interviews and written data on their most active social media site, SinaWeibo. Their socio-biographical data were collected via a questionnaire. A multivariate analysis shows that, rather than there being a simple dominance of either social or cognitive factors, there is an interplay between the two. A speaker’s code-switching corresponds to his/her previous language exposure and use through social networks, but personal attitudes, e.g., a positive view of English, can override network-based predictions of use. Crucially, however, we only see attitude exerting this significant effect within the domain of contexts with low cognitive processing demand (e.g., asynchronous writing).
The findings of this study show that personal preference can indeed override language usage in interactive networks, but such effect is constrained by individual differences in cognitive capacities of processing, which in turn relates back to frequency of usage which automatizes processing. In this way, this study offers a dynamic view of the usage-based account of language by illustrating that social experiences, frequency of usage, attitudes, and language system constantly interact, with frequency of usage playing a central role of relating one to another.
