Vote or not? How language mimicry affect peer recognition in an online social Q&A community

Abstract

As Q&A Communities become not only a source of information, but an interaction platform where people gain social recognition, the research into factors impacting viewers’ peer recognition of online contribution helps identify an effective model for such interaction. This study focuses on finding the connection between language mimicry and the peer recognition of online contributions. We collected a total of 13,109 contributions from Fluther, an online Q&A community. Language features including linguistic similarity, text resemblance and peer recognition of online contributions were analysed, with the contributors’ followers and past responses serving as moderators. Linear regression was adopted to provide empirical evidence. This study demonstrates that language mimicry between the contributor and the information seeker has significant positive effect on the peer recognition of online contributions by the viewers. Moreover, the number of contributors’ past expertise mitigates the positive influence of linguistic similarity and text resemblance while their popularity strengthens the influence. It is a novel direction as prior language mimicry studies mainly focused on dyadic communication, whereas this research study aims to examine the influence of language mimicry on peer recognition of online contribution. The study extends the literature on language mimicry and provides practical implications.