Literature DB >> 34335083

Do New Romantic Couples Use More Similar Language Over Time? Evidence from Intensive Longitudinal Text Messages.

Miriam Brinberg1, Nilam Ram2.   

Abstract

The digital text traces left by computer-mediated communication (CMC) provide a new opportunity to test theories of relational processes that were originally developed through observation of face-to-face interactions. Communication accommodation theory, for example, suggests that conversation partners' verbal (and non-verbal) behaviors become more similar as relationships develop. Using a corpus of 1+ million text messages that 41 college-age romantic couples sent to each other during their first year of dating, this study examines how linguistic alignment of new romantic couples' CMC changes during relationship formation. Results from nonlinear growth models indicate that three aspects of daily linguistic alignment (syntactic-language style matching, semantic-latent semantic analysis, overall-cosine similarity) all exhibit exponential growth to an asymptote as romantic relationships form. Beyond providing empirical support that communication accommodation theory also applies in romantic partners' CMC, this study demonstrates how relational processes can be examined using digital trace data.
© The Author(s) 2021. Published by Oxford University Press on behalf of International Communication Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  Communication Accommodation; Computer-mediated Communication; Intensive Longitudinal Analysis; Linguistic Alignment; Relationship Development; Romantic Relationships

Year:  2021        PMID: 34335083      PMCID: PMC8315721          DOI: 10.1093/joc/jqab012

Source DB:  PubMed          Journal:  J Commun        ISSN: 0021-9916


  11 in total

1.  Language style matching predicts relationship initiation and stability.

Authors:  Molly E Ireland; Richard B Slatcher; Paul W Eastwick; Lauren E Scissors; Eli J Finkel; James W Pennebaker
Journal:  Psychol Sci       Date:  2010-12-13

2.  LSAfun--An R package for computations based on Latent Semantic Analysis.

Authors:  Fritz Günther; Carolin Dudschig; Barbara Kaup
Journal:  Behav Res Methods       Date:  2014-11-26

3.  ALIGN: Analyzing linguistic interactions with generalizable techNiques-A Python library.

Authors:  Nicholas D Duran; Alexandra Paxton; Riccardo Fusaroli
Journal:  Psychol Methods       Date:  2019-02-28

4.  Latent Semantic Analysis: A new measure of patient-physician communication.

Authors:  Scott R Vrana; Dylan T Vrana; Louis A Penner; Susan Eggly; Richard B Slatcher; Nao Hagiwara
Journal:  Soc Sci Med       Date:  2017-12-18       Impact factor: 4.634

5.  Determining synchrony between behavioral time series: An application of surrogate data generation for establishing falsifiable null-hypotheses.

Authors:  Robert G Moulder; Steven M Boker; Fabian Ramseyer; Wolfgang Tschacher
Journal:  Psychol Methods       Date:  2018-03-29

6.  Communication accommodation in text messages: Exploring liking, power, and sex as predictors of textisms.

Authors:  Aubrie Adams; Jai Miles; Norah E Dunbar; Howard Giles
Journal:  J Soc Psychol       Date:  2018-01-17

7.  Mutual influence in expressive behavior: adult--adult and infant--adult dyadic interaction.

Authors:  J N Cappella
Journal:  Psychol Bull       Date:  1981-01       Impact factor: 17.737

8.  The Electronically Activated Recorder (EAR): A Method for the Naturalistic Observation of Daily Social Behavior.

Authors:  Matthias R Mehl
Journal:  Curr Dir Psychol Sci       Date:  2017-04-06

9.  Screenomics: A Framework to Capture and Analyze Personal Life Experiences and the Ways that Technology Shapes Them.

Authors:  Byron Reeves; Nilam Ram; Thomas N Robinson; James J Cummings; C Lee Giles; Jennifer Pan; Agnese Chiatti; M J Cho; Katie Roehrick; Xiao Yang; Anupriya Gagneja; Miriam Brinberg; Daniel Muise; Yingdan Lu; Mufan Luo; Andrew Fitzgerald; Leo Yeykelis
Journal:  Hum Comput Interact       Date:  2019-03-13       Impact factor: 4.750

10.  Data mining for health: staking out the ethical territory of digital phenotyping.

Authors:  Nicole Martinez-Martin; Thomas R Insel; Paul Dagum; Henry T Greely; Mildred K Cho
Journal:  NPJ Digit Med       Date:  2018-12-19
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