Most action in a business context is carried out through language and as such communication can be said to constitute the foundation of organisations. Language is not exclusively a medium through which we transmit information in both spoken and written form but it also contributes to our construction of identity and interpersonal relations. Consequently, language use is a form of social action and when we speak we therefore act. Today we increasingly do so on social media.
Over the last few years, I’ve been researching such speech acts in blogs and microblogs to show how they can be more easily identified in large data collections and how language has adapted to the online environment. While this is of interest regarding language use in general, my most recent research project is specifically aimed at the language used for business communication purposes on social media. Especially in the field of customer communication, it is essential to know which linguistic behaviour triggers positive or negative reactions and how to separate positive from negative comments in a reliable manner.
This is where corpus linguistic studies can help. Corpus linguistics facilitates, on the one hand, the quantitative analysis of large samples of data, while, on the other hand, allowing for the analysis to consider the context in which linguistic constructions appear. Thus, contrary to other methodological approaches, texts are not broken up into single words but studied in their entire, original form. This is important as function words, which are often not regarded as carrying significant meaning, may determine whether a comment is positive or negative (e.g. Your service is shit vs Your new app is the shit, see Lutzky and Kehoe 2016).
In our previous studies, we started out from the concept of collocation, which is the calculation of the probability with which words appear in each other’s vicinity, in order to distinguish between often very different uses of words. We then introduced the new calculation of shared and unique collocates, i.e. the comparison of collocates that a word shares with others and those that distinguish them from each other. This innovative approach to the study of collocation allows for different uses of the same word to be separated in large corpora in order to narrow down the sentiments expressed by bloggers and microbloggers. For more information, see Lutzky and Kehoe (2016, 2017).