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Valence-dependent mutation in lexical evolution

Nature Human Behaviour volume 7, pages 190–199 (2023)Cite this article

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Abstract

A central goal of linguistics is to understand how words evolve. Past research has found that macro-level factors such as frequency of word usage and population size explain the pace of lexical evolution. Here we focus on cognitive and affective factors, testing whether valence (positivity–negativity) explains lexical evolution rates. Using estimates of cognate replacement rates for 200 concepts on an Indo-European language tree spanning six to ten millennia, we find that negative valence correlates with faster cognate replacement. This association holds when controlling for frequency of use, and follow-up analyses show that it is most robust for adjectives (‘dirty’ versus ‘clean’; ‘bad’ versus ‘good’); it does not consistently reach statistical significance for verbs, and never reaches significance for nouns. We also present experiments showing that individuals are more likely to replace words for negative versus positive concepts. Our findings suggest that emotional valence affects micro-level guided variation, which drives macro-level valence-dependent mutation in adjectives.

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Fig. 1: The relationship between semantic valence and cognate replacement rate in four Indo-European languages.
Fig. 2: The meta-analytic relationship between valence and cognate replacement rate for different parts of speech.
Fig. 3: The relationship between population-level cognate replacement and individual-level word replacement.

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Data availability

Our project page at https://osf.io/f86wt/ displays all data from this paper. Our analyses used external data from WOLD (https://wold.clld.org/) and from Pagel, Atkinson and Meade (https://www.nature.com/articles/nature06176?message=remove&pagewanted=all).

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Our project page at https://osf.io/f86wt/ displays all code from this paper.

References

  1. Lewis, M. P. Ethnologue: Languages of the World (SIL International, 2009).

  2. Croft, W. Evolutionary linguistics. Annu. Rev. Anthropol. 37, 219–234 (2008).

    Article  Google Scholar 

  3. Pagel, M. Human language as a culturally transmitted replicator. Nat. Rev. Genet. 10, 405–415 (2009).

    Article  CAS  PubMed  Google Scholar 

  4. Gray, R. D. & Atkinson, Q. D. Language-tree divergence times support the Anatolian theory of Indo-European origin. Nature 426, 435–439 (2003).

    Article  CAS  PubMed  Google Scholar 

  5. Jackson, J. C. et al. From text to thought: how analyzing language can advance psychological science. Perspect. Psychol. Sci. 17, 805–826 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  6. Dor, D. & Jablonka, E. From cultural selection to genetic selection: a framework for the evolution of language. Selection 1, 33–56 (2001).

    Article  Google Scholar 

  7. Jablonka, E. & Lamb, M. J. Précis of evolution in four dimensions. Behav. Brain Sci. 30, 353 (2007).

    Article  PubMed  Google Scholar 

  8. Boyd, R. & Richerson, P. J. Culture and the Evolutionary Process (Univ. Chicago Press, 1988).

  9. Sperber, D. Explaining Culture: A Naturalistic Approach (Blackwell, 1996).

  10. Mesoudi, A. & Whiten, A. The multiple roles of cultural transmission experiments in understanding human cultural evolution. Philos. Trans. R. Soc. B 363, 3489–3501 (2008).

    Article  Google Scholar 

  11. Acerbi, A. & Alexander Bentley, R. Biases in cultural transmission shape the turnover of popular traits. Evol. Hum. Behav. 35, 228–236 (2014).

    Article  Google Scholar 

  12. Bebbington, K., MacLeod, C., Ellison, T. M. & Fay, N. The sky is falling: evidence of a negativity bias in the social transmission of information. Evol. Hum. Behav. 38, 92–101 (2017).

    Article  Google Scholar 

  13. Berger, J. Arousal increases social transmission of information. Psychol. Sci. 22, 891–893 (2011).

    Article  PubMed  Google Scholar 

  14. Pennebaker, J. W., Mehl, M. R. & Niederhoffer, K. G. Psychological aspects of natural language use: our words, our selves. Annu. Rev. Psychol. 54, 547–577 (2003).

    Article  PubMed  Google Scholar 

  15. Nettle, D. Is the rate of linguistic change constant? Lingua 108, 119–136 (1999).

    Article  Google Scholar 

  16. Thomason, S. G. Language change and language contact. Encycl. Lang. Linguist. 6, 339–347 (2006).

    Article  Google Scholar 

  17. Pagel, M., Atkinson, Q. D. & Meade, A. Frequency of word-use predicts rates of lexical evolution throughout Indo-European history. Nature 449, 717–720 (2007).

    Article  CAS  PubMed  Google Scholar 

  18. Wichmann, S. & Holman, E. W. in Approaches to Measuring Linguistic Differences (eds Borin, L. & Saxena, A.) (De Gruyter, 2013).

  19. Monaghan, P. Age of acquisition predicts rate of lexical evolution. Cognition 133, 530–534 (2014).

    Article  PubMed  Google Scholar 

  20. Vejdemo, S. & Hörberg, T. Semantic factors predict the rate of lexical replacement of content words. PLoS ONE 11, e0147924 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Baumeister, R. F., Bratslavsky, E., Finkenauer, C. & Vohs, K. D. Bad is stronger than good. Rev. Gen. Psychol. 5, 323–370 (2001).

    Article  Google Scholar 

  22. Jefferies, L. N., Smilek, D., Eich, E. & Enns, J. T. Emotional valence and arousal interact in attentional control. Psychol. Sci. 19, 290–295 (2008).

    Article  PubMed  Google Scholar 

  23. Kuperman, V., Estes, Z., Brysbaert, M. & Warriner, A. B. Emotion and language: valence and arousal affect word recognition. J. Exp. Psychol. Gen. 143, 1065 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  24. Jackson, J. C. et al. Emotion semantics show both cultural variation and universal structure. Science 366, 1517–1522 (2019).

    Article  CAS  PubMed  Google Scholar 

  25. Di Natale, A., Pellert, M. & Garcia, D. Colexification networks encode affective meaning. Affect. Sci. 2, 99–111 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  26. Eimer, M. & Holmes, A. Event-related brain potential correlates of emotional face processing. Neuropsychologia 45, 15–31 (2007).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Fischler, I. & Bradley, M. Event-related potential studies of language and emotion: words, phrases, and task effects. Prog. Brain Res. 156, 185–203 (2006).

    Article  PubMed  Google Scholar 

  28. Schupp, H. T., Junghöfer, M., Weike, A. I. & Hamm, A. O. The selective processing of briefly presented affective pictures: an ERP analysis. Psychophysiology 41, 441–449 (2004).

    Article  PubMed  Google Scholar 

  29. Osgood, C. E., & Tzeng, O. C. S. (eds). Language, Meaning, and Culture: The Selected Papers of C. E. Osgood (Praeger, 1990).

  30. Bloom, P. How Children Learn the Meanings of Words (MIT Press, 2002).

  31. Broze, Y. & Shanahan, D. Diachronic changes in jazz harmony: a cognitive perspective. Music Percept. Interdiscip. J. 31, 32–45 (2013).

    Article  Google Scholar 

  32. DeWall, C. N., Pond, R. S. Jr, Campbell, W. K. & Twenge, J. M. Tuning in to psychological change: linguistic markers of psychological traits and emotions over time in popular US song lyrics. Psychol. Aesthet. Creat. Arts 5, 200 (2011).

    Article  Google Scholar 

  33. Morin, O. & Acerbi, A. Birth of the cool: a two-centuries decline in emotional expression in Anglophone fiction. Cogn. Emot. 31, 1663–1675 (2017).

    Article  PubMed  Google Scholar 

  34. Pratto, F. & John, O. P. Automatic vigilance: the attention-grabbing power of negative social information. J. Pers. Soc. Psychol. 61, 380 (1991).

    Article  CAS  PubMed  Google Scholar 

  35. Fiske, S. T. Attention and weight in person perception: the impact of negative and extreme behavior. J. Pers. Soc. Psychol. 38, 889 (1980).

    Article  Google Scholar 

  36. Brady, W. J., Crockett, M. J. & Van Bavel, J. J. The MAD model of moral contagion: the role of motivation, attention, and design in the spread of moralized content online. Perspect. Psychol. Sci. 15, 978–1010 (2020).

    Article  PubMed  Google Scholar 

  37. Taylor, S. E. Asymmetrical effects of positive and negative events: the mobilization-minimization hypothesis. Psychol. Bull. 110, 67 (1991).

    Article  CAS  PubMed  Google Scholar 

  38. Bless, H. & Fiedler, K. Mood and the regulation of information processing and behavior. in Affect in Social Thinking and Behavior (ed Forgas, J. P.) 65–84 (Psychology Press, 2006).

  39. Forgas, J. P. Feeling and doing: affective influences on interpersonal behavior. Psychol. Inq. 13, 1–28 (2002).

    Article  Google Scholar 

  40. Schwarz, N. & Bless, H. in Emotion and Social Judgments (ed Forgas, J. P.) 55–71 (Garland Science, 2020).

  41. Matlin, M. W. & Stang, D. J. The Pollyanna Principle: Selectivity in Language, Memory, and Thought (Schenkman, 1978).

  42. Forgas, J. P. Mood and the perception of unusual people: affective asymmetry in memory and social judgments. Eur. J. Soc. Psychol. 22, 531–547 (1992).

    Article  Google Scholar 

  43. Warriner, A. B., Kuperman, V. & Brysbaert, M. Norms of valence, arousal, and dominance for 13,915 English lemmas. Behav. Res. Methods 45, 1191–1207 (2013).

    Article  PubMed  Google Scholar 

  44. Stadthagen-Gonzalez, H. et al. Norms of valence and arousal for 14,031 Spanish words. Behav. Res. Methods 49, 111–123 (2017).

    Article  PubMed  Google Scholar 

  45. Imbir, K. K. Affective norms for 4900 Polish Words Reload (ANPW_R): assessments for valence, arousal, dominance, origin, significance, concreteness, imageability and, age of acquisition. Front. Psychol. 7, 1081 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Moors, A. et al. Norms of valence, arousal, dominance, and age of acquisition for 4,300 Dutch words. Behav. Res. Methods 45, 169–177 (2013).

    Article  PubMed  Google Scholar 

  47. Swadesh, M. Lexico-statistic dating of prehistoric ethnic contacts: with special reference to North American Indians and Eskimos. Proc. Am. Philos. Soc. 96, 452–463 (1952).

    Google Scholar 

  48. Croft, W. Explaining Language Change: An Evolutionary Approach (Pearson Education, 2000).

  49. Enders, C. K. & Tofighi, D. Centering predictor variables in cross-sectional multilevel models: a new look at an old issue. Psychol. Methods 12, 121 (2007).

    Article  PubMed  Google Scholar 

  50. Mulkar-Mehta, R., Hobbs, J. & Hovy, E. Granularity in natural language discourse. In Proc. Ninth International Conference on Computational Semantics (IWCS, 2011).

  51. Smidt, K. E. & Suvak, M. K. A brief, but nuanced, review of emotional granularity and emotion differentiation research. Curr. Opin. Psychol. 3, 48–51 (2015).

    Article  Google Scholar 

  52. Tugade, M. M., Fredrickson, B. L. & Barrett, L. F. Psychological resilience and positive emotional granularity: examining the benefits of positive emotions on coping and health. J. Pers. 72, 1161–1190 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Averill, J. R. A Semantic Atlas of Emotional Concepts (Am. Psychol. Assoc., 1975).

  54. Clore, L. & Ortony, A. in Cognitive Perspectives on Emotion and Motivation (eds Hamilton, V., Bower, G. H. & Frijda, N. H.) 367–397 (Springer, 1988).

  55. Russell, J. A., Fernández-Dols, J. M., Manstead, A. S. R. & Wellenkamp, J. Everyday Conceptions of Emotion (Springer, 1995).

  56. Anderson, N. H. Likableness ratings of 555 personality-trait words. J. Pers. Soc. Psychol. 9, 272–279 (1968).

    Article  CAS  PubMed  Google Scholar 

  57. Alves, H., Koch, A. & Unkelbach, C. Why good is more alike than bad: processing implications. Trends Cogn. Sci. 21, 69–79 (2017).

    Article  PubMed  Google Scholar 

  58. Harper, D. Etymology, origin and meaning of sleazy by etymonline. Online Etymology Dictionary https://www.etymonline.com/word/sleazy (2000).

  59. Ortony, A., Turner, T. J. & Antos, S. J. A puzzle about affect and recognition memory. J. Exp. Psychol. Learn. Mem. Cogn. 9, 725 (1983).

    Article  Google Scholar 

  60. Echterhoff, G., Higgins, E. T., Kopietz, R. & Groll, S. How communication goals determine when audience tuning biases memory. J. Exp. Psychol. Gen. 137, 3 (2008).

    Article  PubMed  Google Scholar 

  61. Echterhoff, G., Higgins, E. T. & Groll, S. Audience-tuning effects on memory: the role of shared reality. J. Pers. Soc. Psychol. 89, 257 (2005).

    Article  PubMed  Google Scholar 

  62. Ye, J., Zhao, L., Huang, Z. & Meng, F. The audience-tuning effect of negative stereotypes in communication. Front. Psychol. 12, 663814 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Bayliss, C. D., Field, D. & Moxon, E. R. The simple sequence contingency loci of Haemophilus influenzae and Neisseria meningitidis. J. Clin. Invest. 107, 657–666 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Lieberman, M. D. Social: Why Our Brains Are Wired to Connect (Crown, 2013).

  65. Davies, M. Corpus del español: 10 billion words: dialects / genres / historical. https://www.corpusdelespanol.org/

  66. Haspelmath, M. & Tadmor, U. Loanwords in the World’s Languages: A Comparative Handbook (Walter de Gruyter, 2009).

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Acknowledgements

J.W. thanks the Marsden Foundation of New Zealand (19-UOO-1932) for funding. The Marsden foundation played no role in the conceptualization, design, analysis or decision to publish this research. The authors thank I. Khismatova for research assistance.

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Authors and Affiliations

  1. Kellogg School of Management, Northwestern University, Evanston, IL, USA

    Joshua Conrad Jackson

  2. Department of Psychology and Neuroscience, University of North Carolina, Chapel Hill, NC, USA

    Kristen Lindquist & Ryan Drabble

  3. School of Psychology, University of Auckland, Auckland, New Zealand

    Quentin Atkinson

  4. Department of Linguistic and Cultural Evolution, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

    Quentin Atkinson & Joseph Watts

  5. Religion Programme, University of Otago, Dunedin, New Zealand

    Joseph Watts

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Contributions

J.C.J. conceptualized the study, analysed the data and co-wrote the manuscript. K.L. co-wrote the manuscript. R.D. collected the data. Q.A. co-wrote the manuscript. J.W. conceptualized the study and co-wrote the manuscript.

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Correspondence to Joshua Conrad Jackson.

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Jackson, J.C., Lindquist, K., Drabble, R. et al. Valence-dependent mutation in lexical evolution. Nat Hum Behav 7, 190–199 (2023). https://doi.org/10.1038/s41562-022-01483-8

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