Language Matters: The Double-Edged Role of Linguistic Style Matching in Work Groups

Abstract

Linguistic style matching (LSM) refers to a similar linguistic style among conversation partners. We examine the effects of LSM on perceived team performance and perceived social support in real work groups. We propose that team tenure moderates the relationship between LSM and perceived performance such that LSM and performance are positively related for teams with low tenure and negatively related for teams with high levels of tenure. We also propose that LSM and perceived social support are positively related. To test the hypotheses, we videotaped and transcribed meetings of 160 researchers, nested in 26 teams, to assess the individual levels of LSM. We measured team performance and social support with questionnaire scales. In partial support of the hypotheses, multilevel models show a negative relationship between LSM and team performance and a positive relationship between LSM and social support. We discuss potential implications for team research and practitioners.

Beyond Consistency: Contextual Dependency of Language Style in Monolog and Conversation

“…Our results fundamentally tell us two things about LS: Having a conversation partner increases our use and structure of function words, leading to a more uniform use of LS. Building on research on language style matching—the process of adapting one’s language style to someone else over the course of a conversation (Müller‐Frommeyer et al, 2019)—these changes might be indicative of an increasing similarity in LS of the conversation partners (e.g., Heuer et al, 2019; Ireland et al, 2011; Niederhoffer & Pennebaker, 2002). Additionally, these results could be reflective of the social nature of LS—two people interacting with each other create their own shared worldview.…”

“…This is a deviation from previous research on specific components of LS, which analyzed all function word categories individually (e.g., Mehl & Pennebaker, 2003). Based on the definition of LS as one construct represented by overall function word use (Chung & Pennebaker, 2007) and the operationalization of LS in existing studies on language style matching (e.g., Gonzales et al, 2010; Heuer et al, 2019), we chose this approach as we are interested in the changes in overall LS use. However, we acknowledge that previous research found significant differences in the use and function of individual function word categories (e.g., Pennebaker, 2013).…”

“…Finally, we only investigated two social settings, comparing language production in isolation to dyadic interaction. As processes of LS alignment are also present in interactions of more than two people (e.g., in groups and teams; Gonzales et al, 2010; Heuer et al, 2019), future work should additionally examine these settings.…”

“…In the German dictionary, the broad function word category is a combination of its subcategories: pronouns, articles, prepositions, auxiliary verbs, adverbs, conjunctions, and negations. With the new innovative methodological approach and the exploratory nature of this approach, we are predominantly interested in the changes in overall function word use (e.g., Gonzales, Hancock, & Pennebaker, 2010; Heuer, Müller‐Frommeyer, & Kauffeld, 2019). Therefore, in the current paper, we analyzed the broad function word category.…”

Approaches for assessing communication in human-autonomy teams

“…In doing so, people engaged in a conversation (speakers) may exhibit similar lexical (i.e., word choice) and syntactic (i.e., sentence structure) properties in their utterances, presumably because greater lexical and syntactic alignment improves efficiency in communication (Semin 2007). In fact, many scholars have examined linguistic similarity among speakers, revealing positive associations with cohesion (Dong 2005;Heuer et al 2020), trust (Scissors et al 2009), and task performance (Dong et al 2004;Foltz et al 2003;Fusaroli et al 2012;Gorman et al 2003;Richardson et al 2019;Yilmaz 2016). Here, we outline approaches which have yielded some promising results in human-human teams, including their computation, relevant findings in the literature, and how they may be adapted and improved for understanding cohesion, trust, and performance in human-autonomy teams.…”