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Internet Pragmatics: Online-First Articles

Psychophysiological effects of evaluative language use on Twitter complaints and compliments

| KU Leuven
| Ghent University
| Ghent University
This article explores the role of evaluative language in the identification of emotions in–and psychophysiological responses to–Twitter complaints and compliments by the readers of these messages. Three hypotheses were tested in this research. First, in line with recent experimental work in French, we expected the presence of negative evaluative language in complaints to increase perceived dissatisfaction, impoliteness, and offensiveness by the reader. Second, assuming the negativity bias hypothesis, stronger psychophysiological responses should be found in complaints compared to compliments. Third, readers’ psychophysiological responses should be stronger for complaints and compliments including evaluative language. To test these hypotheses, we used a reading task involving cardiovascular reactivity measurements and a questionnaire. We found that perceived customer dissatisfaction, impoliteness and offensiveness were higher in complaints with vs. without evaluative language. We did not find an effect of the negativity bias on cardiovascular reactivity. Rather, compliments with evaluative language elicited larger cardiac slowing compared to complaints (with or without evaluative language) and compliments without evaluative language. As the stimuli is our study concern a railway company (which is mostly the target of criticism and complaints on Twitter), participants may have reacted more to the sort of feedback they would not expect the company to receive. Future research will be necessary to establish whether our findings still hold in the case of companies that achieve a better balance between negative and positive feedback.
Keywords: Twitter, complaints, compliments, (im)politeness, customer dissatisfaction, psychophysiology
Article outline
  • 1.Introduction
  • 2.Literature review
  • 3.Theoretical foundations
  • 4.Predictions
  • 5.Experimental study
    • 5.1Materials
    • 5.2Participants and procedure
    • 5.3Methods for data analysis
    • 5.4Results
      • 5.4.1Questionnaire
      • 5.4.2Reading task
  • 6.General discussion
  • 7.Conclusions
  • Notes
  • References
Available under the Creative Commons Attribution (CC BY) 4.0 license.

For any use beyond this license, please contact the publisher at rights@benjamins.nl.

Published online: 20 July 2023
DOI logo
https://doi.org/10.1075/ip.00092.ruy
References
Barsade, Sigal G.
2002 “The ripple effect: Emotional contagion and its influence on group behavior.” Administrative Science Quarterly 47(4): 644–675. DOI logoGoogle Scholar
Baumeister, Roy F., Ellen Bratslavsky, Catrin Finkenauer, and Kathleen D. Vohs
2001 “Bad is stronger than good.” Review of General Psychology 5(4): 323–370. DOI logoGoogle Scholar
Berger, Jonah
2013 “Beyond viral: Interpersonal communication in the Internet age.” Psychological Inquiry 24(4): 293–296. DOI logoGoogle Scholar
Bianchin, Marta, and Alessandro Angrilli
2012 “Gender differences in emotional responses: A psychophysiological study.” Physiology and Behavior 105(4): 925–932. DOI logoGoogle Scholar
Brassen, Stefanie, Matthias Gamer, Jan Peters, Sebastian Gluth, and Christian Buchel
2012 “Don’t look back in anger! Responsiveness to missed chances in successful and nonsuccessful aging.” Science 336(6081): 612–614. DOI logoGoogle Scholar
Brown, Penelope, and Stephen C. Levinson
1987 Politeness: Some Universals in Language Usage. Cambridge: Cambridge University Press. DOI logoGoogle Scholar
Campbell, Jana, and Ulrike Ehlert
2012 “Acute psychosocial stress: Does the emotional stress response correspond with physiological responses?” Psychoneuroendocrinology 37(8): 1111–1134. DOI logoGoogle Scholar
Cenni, Irene, and Patrick Goethals
2017 “Negative hotel reviews on TripAdvisor: A cross-linguistic analysis.” Discourse, Context & Media 161: 22–30. DOI logoGoogle Scholar
Cenni, Irene, and Camilla Vásquez
2022 “ ‘Jerry was a terrific host!’ ‘You were a brilliant guest!’: Reciprocal compliments on Airbnb.” Pragmatics and Society 14(1): 117–142. DOI logoGoogle Scholar
Codispoti, Maurizio, Paola Surcinelli, and Bruno Baldaro
2008 “Watching emotional movies: Affective reactions and gender differences.” International Journal of Psychophysiology 69(2): 90–95. DOI logoGoogle Scholar
Decock, Sofie
2022 “Discursive approaches to webcare: A closer look at apologies, conversational humanvoice, legitimation, and emotion regulation.” Discourse, Context &Media 451, 100575. DOI logoGoogle Scholar
Decock, Sofie, and Ilse Depraetere
2018 “(In)directness and complaints: A reassessment.” Journal of Pragmatics 1321: 33–46. DOI logoGoogle Scholar
Decock, Sofie, Bernard De Clerck, Chloé Lybaert, and Koen Plevoets
2021 “Testing the various guises of Conversational Human Voice: The impact of formality and personalization on customer outcomes in online complaint management.” Journal of Internet Commerce 20(1): 1–24. DOI logoGoogle Scholar
Depraetere, Ilse, Sofie Decock, and Nicolas Ruytenbeek
2021 “Linguistic (in)directness in Twitter complaints: A contrastive analysis of railway complaint interactions.” Journal of Pragmatics 1711: 215–233. DOI logoGoogle Scholar
Epel, Elissa S., Alexandra D. Crosswell, Stefanie E. Mayer, Aric A. Prather, George M. Slavich, Eli Puterman, and Wendy B. Mendes
2018 “More than a feeling: A unified view of stress measurement for population science.” Frontiers in Neuroendocrinology 491: 146–169. DOI logoGoogle Scholar
Felbermayr, Armin, and Alexandros Nanopoulos
2016 “The role of emotions for the perceived usefulness in online customer reviews.” Journal of Interactive Marketing 36(1): 60–76. DOI logoGoogle Scholar
Ferrara, Emilio, and Zeyao Yang
2015 “Measuring emotional contagion in social media.” PloS one 10(11), e0142390. DOI logoGoogle Scholar
Fox, Alexa K., George D. Deitz, Marla B. Royne, and Joseph D. Fox
2018 “The face of contagion: Consumer response to service failure depiction in online reviews.” European Journal of Marketing 52(1/2): 39–65. DOI logoGoogle Scholar
Franzke, Aline S., Anja Bechmann, Michael Zimmer, Charles M. Ess, and the Association of Internet Researchers
2020 “Internet research: Ethical guidelines 3.0.” [URL] (accessed 3 March 2021).
Garfinkel, Sarah N., and Hugo D. Critchley
2016 “Threat and the body: How the heart supports fear processing.” Trends in Cognitive Sciences 20(1): 34–46. DOI logoGoogle Scholar
Goldenberg, Amit, and James J. Gross
2020 “Digital emotion contagion.” Trends in Cognitive Sciences 24(4): 316–328. DOI logoGoogle Scholar
Gray, Marcus A., Felix D. Beacher, Ludovico Minati, Yoko Nagai, Andrew H. Kemp, Neil A. Harrison, and Hugo D. Critchley
2012 “Emotional appraisal is influenced by cardiac afferent information.” Emotion 12(1): 180–191. DOI logoGoogle Scholar
Gunther Moor, Bregtje, Linda van Leijenhorst, Serge A. R. B. Rombouts, Eveline A. Crone, and Mauritz W. Van der Molen
2010 “Do you like me? Neural correlates of social evaluation and developmental trajectories.” Social Neuroscience 5(5–6): 461–482. DOI logoGoogle Scholar
Guo, Junpeng, Xiaopan Wang, and Yi Wu
2020 “Positive emotion bias: Role of emotional content from online customer reviews in purchase decisions.” Journal of Retailing and Consumer Services 521, 101891. DOI logoGoogle Scholar
Hatfield, Elaine, John T. Cacioppo, and Richard L. Rapson
1994 Emotional Contagion. New York: Cambridge University Press.Google Scholar
Holmqvist, Jonas, and Christian Grönroos
2012 “How does language matter for services? Challenges and propositions for service research.” Journal of Service Research 15(4): 430–442. DOI logoGoogle Scholar
Holmqvist, Jonas, Yves Van Vaerenbergh, Renaud Lunardo, and Micael Dahlén
2019 “The language backfire effect: How frontline employees decrease customer satisfaction through language use.” Journal of Retailing 95(2): 115–129. DOI logoGoogle Scholar
Ito, Tiffany A., Jeff T. Larsen, N. Kyle Smith, and John T. Cacioppo
1998 “Negative information weighs more heavily on the brain: The negativity bias in evaluative categorizations.” Journal of Personality and Social Psychology 75(4): 887–900. DOI logoGoogle Scholar
Jennings, J. Richard
1986 “Do cardiovascular changes indicate energetic support of information processing?” In Energetics and Human Information Processing, ed. by G. M. Hockey, Anthony W. K. Gaillard, and Michael G. H. Coles, 199–216. Dordrecht: Springer. DOI logoGoogle Scholar
Kuznetsova, Alexandra, Per B. Brockhoff, and Rune H. B. Christensen
2017 “lmerTest package: Tests in linear mixed effects models.” Journal of Statistical Software 82(13): 1–26. DOI logoGoogle Scholar
Labouvie-Vief, Gisela, Mark A. Lumley, Elizabeth Jain, and Hillary Heinze
2003 “Age and gender differences in cardiac reactivity and subjective emotion responses to emotional autobiographical memories.” Emotion 3(2): 115–126. DOI logoGoogle Scholar
Liebrecht, Christine, Lettica Hustinx, and Margot van Mulken
2019 “The relative power of negativity: The influence of language intensity on perceived strength.” Journal of Language and Social Psychology 38(2): 170–193. DOI logoGoogle Scholar
Ludwig, Stephan, Ko de Ruyter, Mike Friedman, Elisabeth C. Brüggen, Martin Wetzels, and Gerard Pfann
2013 “More than words: The influence of affective content and linguistic style matches in online reviews on conversion rates.” Journal of Marketing 77(1): 87–103. DOI logoGoogle Scholar
Lutzky, Ursula
2021 The Discourse of Customer Service Tweets. London: Bloomsbury. DOI logoGoogle Scholar
Lybaert, Chloé, Bernard De Clerck, Koen Plevoets, Tess Loete, and Sofie Depovere
2020 “De impact van taal en gender in negatieve reviews: Een experimentele studie naar gepercipieerde geloofwaardigheid en consumentengedrag.” [The impact of language and gender in negative reviews: An experimental study of perceived trustworthiness and consumer behavior]. Tijdschrift van Taalbeheersing 42(1): 55–94. DOI logoGoogle Scholar
Meinl, Marja E.
2010 “Electronic complaints: An empirical study on British English and German complaints on eBay.” PhD dissertation, University of Bonn.
Mendes, Wendy B., Jim Blascovich, Sarah B. Hunter, Brian Lickel, and John T. Jost
2007 “Threatened bythe unexpected: Physiological responses during social interactions with expectancy-violating partners.” Journal of Personality and Social Psychology 92(4): 698–716. DOI logoGoogle Scholar
Oliveira-Silva, Patrícia, and Oscar F. Gonçalves
2011 “Responding empathically: A question of heart, not a question of skin.” Applied Psychophysiology and Biofeedback 36(3): 201–207. DOI logoGoogle Scholar
Ott, Larissa, and Petra Theunissen
2015 “Reputations at risk: Engagement during social media crises.” Public Relations Review 41(1): 97–102. DOI logoGoogle Scholar
Placencia, María E., and Zohreh R. Eslami
(eds) 2020 Complimenting Behaviour and (Self-) Praise acrossSocial Media: New Contexts and New Insights. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Placencia, María E., and Amanda Lower
2017 “Compliments and compliment responses.” In Pragmatics of Social Media, ed. by Christian Hoffmann, and Wolfram Bublitz, 633–660. Berlin: De Gruyter. DOI logoGoogle Scholar
Porges, Stephen W.
2006 “Emotion: An evolutionary by-product of the neural regulation of the autonomic nervous system.” Annals of the New York Academy of Sciences 807(1): 62–77. DOI logoGoogle Scholar
Prkachin, Kenneth M., Rhonda M. Williams-Avery, Caroline Zwaal, and David E. Mills
1999 “Cardiovascular changes during induced emotion: An application of Lang’s theory of emotional imagery.” Journal of Psychosomatic Research 47(3): 255–267. DOI logoGoogle Scholar
Psychology Software Tools, Inc.
2016 “E-Prime” (Version 3.0) [Computer software]. [URL] (accessed 20 August 2021).
Raizen, Adina, Nikos Vergis, and Kiel Christianson
2015 “Using eye-tracking to examine the reading of texts containing taboo words.” In Interdisciplinary Perspectives on Im/politeness, ed. by Marina Terkourafi, and Staci Defibaugh, 213–238. Amsterdam: John Benjamins. DOI logoGoogle Scholar
Rattel, Julina A., Iris B. Mauss, Michael Liedlgruber, and Frank H. Wilhelm
2020 “Sex differences in emotional concordance.” Biological Psychology 1511, 107845. DOI logoGoogle Scholar
R Core Team
2019 R: A Language and Environment for Statistical Computing. Vienna: R Foundation for Statistical Computing. [URL].Google Scholar
Ren, Fuji, and Changqin Quan
2012 “Linguistic-based emotion analysis and recognition for measuring consumer satisfaction: An application of affective computing.” Information Technology and Management 13(4): 321–332. DOI logoGoogle Scholar
Rozin, Paul, and Edward B. Royzman
2001 “Bias, negativity dominance, and contagion.” Personality and Social Psychology Review 5(4): 296–320. DOI logoGoogle Scholar
Ruytenbeek, Nicolas, Sofie Decock, and Ilse Depraetere
2023a “Experiments into the influence of linguistic (in)directness on perceived face-threat in Twitter complaints.” Journal of Politeness Research 19(1): 59–86. DOI logoGoogle Scholar
2023b “The impact of linguistic choices and (para-) linguistic markers on the perception of Twitter complaints by other customers: An experimental approach.” Journal of Politeness Research 19(1): 87–122. DOI logoGoogle Scholar
Ruytenbeek, Nicolas, Marie Verschraegen, and Sofie Decock
2021 “Exploring the impact of platforms’ affordances on the expression of negativity in online negative hotel reviews.” Journal of Pragmatics 1861: 289–307. DOI logoGoogle Scholar
Schellekens, Gaby A. C., Peeter W. J. Verlegh, and Ale Smidts
2012 “Linguistic biases and persuasion in communication about objects.” Journal of Language and Social Psychology 32(3): 291–310. DOI logoGoogle Scholar
Schoenewolf, Gerald
1990 “Emotional contagion: Behavioral induction in individuals and groups.” Modern Psychoanalysis 151: 49–61.Google Scholar
Shiota, Michelle N., Samantha L. Neufeld, Wan H. Yeung, Stephanie E. Moser, and Elaine F. Perea
2011 “Feeling good: autonomic nervous system responding in five positive emotions.” Emotion 11(6): 1368–1378. DOI logoGoogle Scholar
Sigona, Annalise
2015 “Impression management on Facebook and Twitter: Where are people more likely to share positivity or negativity with their audiences?” Young Scholars In Writing 121: 134–141.Google Scholar
Sjak-Shie, Elio E.
2022 PhysioData Toolbox (Version 0.6.3) [Computer software]. Retrieved from [URL]
Smith, Andrew N., Eileen Fischer, and Chen Yongjian
2012 “How does brand-related user-generated content differ across YouTube, Facebook, and Twitter?” Journal of Interactive Marketing 26(2): 102–113. DOI logoGoogle Scholar
Stoet, Gijsbert
2010 “PsyToolkit – A software package for programming psychological experiments using Linux.” Behavior Research Methods 42(4): 1096–1104. DOI logoGoogle Scholar
2017 “PsyToolkit: A novel web-based method for running online questionnaires and reaction-time experiments.” Teaching of Psychology 44(1): 24–31. DOI logoGoogle Scholar
Torre, Jared B., and Matthew D. Lieberman
2018 “Putting feelings into words: Affect labeling as implicit emotion regulation.” Emotion Review 10(2): 116–124. DOI logoGoogle Scholar
Trosborg, Anna
1995 Interlanguage Pragmatics: Requests, Complaints and Apologies. Berlin: Mouton de Gruyter. DOI logoGoogle Scholar
Van der Veen, Frederik M., Anastasiya Burdzina, and Sandra J. E. Langeslag
2019 “Don’t you want me, baby? Cardiac and electrocortical concomitants of romantic interest and rejection.” Biological Psychology 1461, 107707. DOI logoGoogle Scholar
Van der Veen, Frederik M., Maurits W. van der Molen, Priya P. Sahibdin, and Ingmar Franken
2014 “The heart-break of social rejection versus the brain wave of social acceptance.” Social Cognitive and Affective Neuroscience 9(9): 1346–1351. DOI logoGoogle Scholar
Van der Veen, Frederik M., Melle J. W. van der Molen, Maurits W. van der Molen, and Ingmar H. A. Franken
2016 “Thumbs up or thumbs down? Effects of neuroticism and depressive symptoms on psychophysiological responses to social evaluation in healthy students.” Cognitive, Affective, & Behavioral Neuroscience 161: 836–847. DOI logoGoogle Scholar
Vásquez, Camilla
2011 “Complaints online: The case of TripAdvisor.” Journal of Pragmatics 431: 1707–1717. DOI logoGoogle Scholar
2014 The Discourse of Online Consumer Reviews. London: Bloomsbury. DOI logoGoogle Scholar
Vermeulen, Ivar E., and Daphne Seegers
2009 “Tried and tested: The impact of online hotel reviews on consumer consideration.” Tourism Management 30(1): 123–127. DOI logoGoogle Scholar
Von Helversen, Bettina, Katarzyna Abramczuk, Wiesław Kopeć, and Radoslaw Nielek
2018 “Influence of consumer reviews on online purchasing decisions in older and younger adults.” Decision Support Systems 1131: 1–10. DOI logoGoogle Scholar
Widdershoven, Svenja
2019 “Disentangling a web of emotions: The pervasiveness of emotional contagion on social media in service settings.” PhD dissertation, Radboud University of Nijmegen.
Widdershoven, Svenja, Mark Pluymaekers, José Bloemer, Haithem Zourrig, and Paul Sinclair
In press. “Calming the storm: How non-negative messages from fellow consumers can dispel negativity in a social media firestorm.” International Journal of Business Communication.
Yin, Dezhi, Samuel D. Bond, and Han Zhang
2014 “Anxious or angry? Effects of discrete emotions on the perceived helpfulness of online reviews.” MIS Quarterly 38(2): 539–560. DOI logoGoogle Scholar
Zhuo, Jing-Schmidt
2007 “Negativity bias in language: A cognitive-affective model of emotive intensifiers.” Cognitive Linguistics 18(3): 417–443. DOI logoGoogle Scholar