Linguistic Style Matching in Social Interaction

By Kate Niederhoffer, James W. Pennebaker. 2002

577 citations recorded by the source corpus.

Subfields: Experimental and Cognitive Psychology, Language and Linguistics, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/5d3fa586f94bc8964a39bcedc52a54ef1b1fe39f

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In Experimental and Cognitive Psychology

In Language and Linguistics

In Human-Computer Interaction

Citations in the corpus

Linguistic Style Matching and Negotiation Outcome (2005, unknown): “This hypothesis rests on the notion that individuals’ use of words and phrases reflects their global perception of a situation and their explicit concerns and goals at any moment in time (Niederhoffer & Pennebaker, 2002; Taylor, 2002b).”
Computational Sociolinguistics: A Survey (2016, methodology): “Linguistic Inquiry and Word Count (LIWC) has frequently been employed in these studies to capture stylistic accommodation, for example reflected in the use of pronouns [48, 49, 131, 191].”
Pronoun Use Reflects Standings in Social Hierarchies (2014, methodology): “They then completed the Interaction Rating Questionnaire (Niederhoffer& Pennebaker, 2002).”
Language use as a reflection of socialization in online communities (2011, background): “Niederhoffer and Pennebaker (2002) found linguistic style matching both at the conversation level and locally at a turn-by-turn level in dyadic conversations.”
Does It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework (2021, methodology): “have previously been used as style features (Niederhoffer and Pennebaker, 2002).”
Controlling Linguistic Style Aspects in Neural Language Generation (2017, background): “In a text generation system, it is desirable to have control over such stylistic aspects of the text: style variations are used to express the social meanings of a message, and controlling the style of a text is necessary for appropriately conveying a message in a way that is adequate to the social ”
Language Style Matching as a Predictor of Social Dynamics in Small Groups (2010, methodology): “Previous research has provided evidence of mimicry in computer-mediated interactions (Niederhoffer & Pennebaker, 2002), although it is unclear how mimicry in computer-mediated interactions compares with FTF interaction.”
Measuring Acoustic-Prosodic Entrainment with Respect to Multiple Levels and Dimensions (2011, background): “[5] K. G. Niederhoffer and J. W. Pennebaker, “Linguistic style matching in social interaction,” Journal of Language and Social Psychology, vol. 21, no. 4, pp. 337–360, 2002.”
Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation (2017, background): “…relevant to interactive systems, is adaptivity, that is, the way speakers (or systems) alter their lingiuistic choices as a result of their interlocutors’ utterances (Clark, 1996; Niederhoffer & Pennebaker, 2002; Pickering & Garrod, 2004), a theme that has also begun to be explored in nlg”
The antecedents and consequences of human behavioral mimicry. (2013, background): “…findings to demonstrate that people also mimic the general linguistic style of others, including number of spoken words and the degree to which different types of words are utilized (e.g., prepositions, past tense verbs, function words; Ireland & Pennebaker 2010, Niederhoffer & Pennebaker 2002).”
Automatic deception detection in Italian court cases (2013, background): “Researchers working in other fields (not deception detection) evaluated the degree to which people coordinate their speech in dyadic interactions (Ireland et al. 2011; Niederhoffer and Pennebaker 2002): their approach could possibly be applied for feature selection in deception detection as well.”
Winning Arguments: Interaction Dynamics and Persuasion Strategies in Good-faith Online Discussions (2016, background): “While stopwords may be related to how challengers coordinate their style with the OP [14, 35], content words can be a good signal of new information or new perspectives.”