Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Historical analysis of national subjective wellbeing using millions of digitized books

Nature Human Behaviour volume 3, pages 1271–1275 (2019)Cite this article

Subjects

An Author Correction to this article was published on 14 November 2019

This article has been updated

Abstract

In addition to improving quality of life, higher subjective wellbeing leads to fewer health problems and higher productivity, making subjective wellbeing a focal issue among researchers and governments. However, it is difficult to estimate how happy people were during previous centuries. Here we show that a method based on the quantitative analysis of natural language published over the past 200 years captures reliable patterns in historical subjective wellbeing. Using sentiment analysis on the basis of psychological valence norms, we compute a national valence index for the United Kingdom, the United States, Germany and Italy, indicating relative happiness in response to national and international wars and in comparison to historical trends in longevity and gross domestic product. We validate our method using Eurobarometer survey data from the 1970s and demonstrate robustness using words with stable historical meanings, diverse corpora (newspapers, magazines and books) and additional word norms. By providing a window on quantitative historical psychology, this approach could inform policy and economic history.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Correlation of the NVI and aggregate life satisfaction data from the Eurobarometer survey.
Fig. 2: NVI through the period 1820–2009.

Similar content being viewed by others

Data availability

The data necessary to reproduce the analyses presented in this article are provided at https://github.com/warwickpsych/NationalValenceIndex.

Code availability

The code necessary to reproduce the analyses presented in this article is provided at https://github.com/warwickpsych/NationalValenceIndex.

Change history

  • 14 November 2019

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

References

  1. Di Tella, R., MacCulloch, R. J. & Oswald, A. J. Preferences over inflation and unemployment: evidence from surveys of happiness. Am. Econ. Rev. 91, 335–341 (2001).

    Article  Google Scholar 

  2. Deaton, A. Income, health, and well-being around the world: evidence from the Gallup world poll. J. Econ. Perspect. 22, 53–72 (2008).

    Article  Google Scholar 

  3. Stevenson, B. & Wolfers, J. Economic growth and subjective well-being: reassessing the Easterlin paradox. Brookings Pap. Econ. Ac. 39, 1–87 (2008).

    Google Scholar 

  4. Benjamin, D. J., Kimball, M. S., Heffetz, O. & Rees-Jones, A. What do you think would make you happier? What do you think you would choose? Am. Econ. Rev. 102, 2083–2110 (2012).

    Article  Google Scholar 

  5. Proto, E. & Rustichini, A. A reassessment of the relationship between GDP and life satisfaction. PLoS One 8, e79358 (2013).

    Article  Google Scholar 

  6. Bolt, J. & van Zanden, J. L. The Maddison Project: collaborative research on historical national accounts. Econ. Hist. Rev. 67, 627–651 (2014).

    Google Scholar 

  7. Broadberry, S., Campbell, B., Klein, A., Overton, M. & Van Leeuwen, B. British Economic Growth, 1270–1870: An Output-Based Approach School of Economics Discussion Paper http://hdl.handle.net/10871/13984 (University of Exeter, 2012).

  8. Lin, Y. et al. Syntactic annotations for the Google Books Ngram Corpus. In Proc. ACL 2012 System Demonstrations 169–174 (Association for Computational Linguistics, 2012).

  9. Michel, J.-B. et al. Quantitative analysis of culture using millions of digitized books. Science 331, 176–182 (2011).

    Article  CAS  Google Scholar 

  10. Connor, B., Balasubramanyan, R., Routledge, B. R. & Smith, N. A. From tweets to polls: linking text sentiment to public opinion time series. International Conference on Web and Social Media, North America (ICWSM) 11, 122–129 (AAAI, 2010).

  11. Bollen, J., Mao, H. & Zeng, X. Twitter mood predicts the stock market. J. Comput. Sci. 2, 1–8 (2011).

    Article  Google Scholar 

  12. Golder, S. A. & Macy, M. W. Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures. Science 333, 1878–1881 (2011).

    Article  CAS  Google Scholar 

  13. Chmiel, A. et al. Collective emotions online and their influence on community life. PLoS One 6, e22207 (2011).

    Article  CAS  Google Scholar 

  14. Eichstaedt, J. et al. Facebook language predicts depression in medical records. Proc. Natl Acad. Sci. USA 115, 11203–11208 (2018).

    Article  CAS  Google Scholar 

  15. Dodds, P. S., Harris, K. D., Kloumann, I. M., Bliss, C. A. & Danforth, C. M. Temporal patterns of happiness and information in a global social network: hedonometrics and Twitter. PLoS One 6, e26752 (2011).

    Article  CAS  Google Scholar 

  16. Thelwall, M., Buckley, K. & Paltoglou, G. Sentiment in Twitter events. J. Am. Soc. Inf. Sci. Technol. 62, 406–418 (2011).

    Article  Google Scholar 

  17. Nguyen, T., Phung, D., Adams, B., Tran, T. & Venkatesh, S. Classification and pattern discovery of mood in weblogs. Adv. Knowl. Discov. Data Min. 6119, 283–290 (2010).

  18. Feenstra, R. C., Inklaar, R. & Timmer, M. P. The next generation of the Penn World Table. Am. Econ. Rev. 105, 3150–3182 (2015).

    Article  Google Scholar 

  19. van Zanden, J. L. et al. How Was Life? Global Well-Being Since 1820 (OECD Publishing, 2014).

  20. Easterlin, R. A. Does economic growth improve the human lot? Some empirical evidence. Nations Househ. Econ. Growth 89, 89–125 (1974).

    Google Scholar 

  21. Easterlin, R. A., McVey, L. A., Switek, M., Sawangfa, O. & Zweig, J. S. The happiness–income paradox revisited. Proc. Natl Acad. Sci. USA 107, 22463–22468 (2010).

    Article  CAS  Google Scholar 

  22. Kahneman, D. & Deaton, A. High income improves evaluation of life but not emotional well-being. Proc. Natl Acad. Sci. USA 107, 16489–16493 (2010).

    Article  CAS  Google Scholar 

  23. Hills, T. T. The dark side of information proliferation. Perspect. Psychol. Sci. 14, 323–330 (2019).

    Article  Google Scholar 

  24. Li, Y., Engelthaler, T., Siew, C. S. & Hills, T. T. The macroscope: a tool for examining the historical structure of language. Behav. Res. Methods 51, 1864–1877 (2019).

  25. Hills, T. T. & Adelman, J. S. Recent evolution of learnability in American English from 1800 to 2000. Cognition 143, 87–92 (2015).

    Article  Google Scholar 

  26. Jerven, M. An unlevel playing field: national income estimates and reciprocal comparison in global economic history. J. Glob. Hist. 7, 107–128 (2012).

    Article  Google Scholar 

  27. Bradley, M. M. & Lang, P. J. Affective Norms for English Words (ANEW): Instruction Manual and Affective Ratings Technical Report C-1 (The Center for Research in Psychophysiology, Univ. Florida, 1999).

  28. Nielsen, F. Å. A new ANEW: evaluation of a word list for sentiment analysis in microblogs. in Proceedings of the ESWC2011 Workshop on ‘Making Sense of Microposts’: Big things come in small packages 93–98 http://arxiv.org/abs/1103.2903 (2011).

  29. 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  Google Scholar 

  30. Schmidtke, D. S., Schröder, T., Jacobs, A. M. & Conrad, M. ANGST: affective norms for German sentiment terms, derived from the Affective Norms for English Words. Behav. Res. Methods 46, 1108–1118 (2014).

    Article  Google Scholar 

  31. Montefinese, M., Ambrosini, E., Fairfield, B. & Mammarella, N. The adaptation of the Affective Norms for English Words (ANEW) for Italian. Behav. Res. Methods 46, 887–903 (2014).

    Article  Google Scholar 

  32. Greenfield, P. M. The changing psychology of culture from 1800 through 2000. Psychol. Sci. 24, 1722–1731 (2013).

    Article  Google Scholar 

Download references

Acknowledgements

We thank colleagues for discussions on this research, especially S. Allen, S. Becker, S. Broadberry, N. Crafts, R. Duch, A. Oswald, L. Pascali, G. Ricco, D. Ronayne, J. Smith and T. Van Rens; and T. Engelthaler and L. Ying for research assistance. This work was supported by a Royal Society Wolfson Research Merit Award WM160074 (to T.T.H.), the Alan Turing Institute (to T.T.H. and C.I.S.), and The Center for Competitive Advantage in the Global Economy at the University of Warwick (to D.S. and E.P.). This research used cloud computing resources kindly provided through a Microsoft Azure for Research Award. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Author information

Author notes

  1. Eugenio Proto

    Present address: Adam Smith Business School, University of Glasgow, Glasgow, UK

Authors and Affiliations

  1. Department of Psychology and CAGE, University of Warwick, Coventry, UK

    Thomas T. Hills

  2. The Alan Turing Institute, British Library, London, UK

    Thomas T. Hills & Chanuki Illushka Seresinhe

  3. IZA Institute of Labor Economics, Bonn, Germany

    Eugenio Proto & Daniel Sgroi

  4. CESifo, Munich, Germany

    Eugenio Proto

  5. Department of Economics and CAGE, University of Warwick, IZA, Coventry, UK

    Daniel Sgroi

Authors
  1. Thomas T. Hills
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Eugenio Proto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Daniel Sgroi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chanuki Illushka Seresinhe
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

T.T.H., E.P., D.S. and C.I.S. were involved in the study design, project planning, data analysis and writing the manuscript.

Corresponding author

Correspondence to Thomas T. Hills.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary Handling Editor: Stavroula Kousta.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Notes, Supplementary Figs. 1–9, Supplementary Tables 1–15 and Supplementary References.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hills, T.T., Proto, E., Sgroi, D. et al. Historical analysis of national subjective wellbeing using millions of digitized books. Nat Hum Behav 3, 1271–1275 (2019). https://doi.org/10.1038/s41562-019-0750-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-019-0750-z

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing