Skip to main content
Log in

Can Well-Being be Measured Using Facebook Status Updates? Validation of Facebook’s Gross National Happiness Index

  • Published:
Social Indicators Research Aims and scope Submit manuscript

Abstract

Facebook’s Gross National Happiness (FGNH) indexes the positive and negative words used in the millions of status updates submitted daily by Facebook users. FGNH has face validity: it shows a weekly cycle and increases on national holidays. Also, happier individuals use more positive words and fewer negative words in their status updates (Kramer 2010). We examined the validity of FGNH in measuring mood and well-being by comparing it with scores on Diener’s Satisfaction with Life Scale (SWLS), administered to an average of 34 Facebook users every day for a year, then aggregated by day, week, month, quarter and half year. FGNH and SWLS were not significantly correlated, with a negative correlation coefficient. Also, aggregated SWLS scores showed a positive relationship with numbers of negative words in status updates. We conclude that FGNH is a valid measure for neither mood nor well-being; however, it may play a role in mood regulation. This challenges the assumption that linguistic analysis of internet messages is related to underlying psychological states.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Bates, W. (2009). Gross National Happiness. Asian-Pacific Economic Literature, 23(2), 1–16. doi:10.1111/j.1467-8411.2009.01235.x.

    Article  Google Scholar 

  • Baumeister, R. F., & Vohs, K. D. (2004). Handbook of self-regulation: Research theory, and applications. New York: Guilford Press.

    Google Scholar 

  • Charles, A. S. (2008). (Tell me why) I don’t like mondays: Does an overvaluation of future discretionary time underlie reported weekly mood cycles? Cognition and Emotion, 22(7), 1228–1252.

    Article  Google Scholar 

  • Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95, 542–575.

    Article  Google Scholar 

  • Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of Personality and Social Psychology, 69, 71–75.

    Google Scholar 

  • Facebook Data Team. (2010). Continuing our study of happiness, from http://www.facebook.com/notes/facebook-data-team/continuing-our-study-of-happiness/375901788858.

  • Facebook Data Team. (2011). Gross National Happiness, from http://apps.facebook.com/gnh_index/.

  • Gamon, M. (2004). Sentiment classification on customer feedback data: Noisy data, large feature vectors, and the role of linguistic analysis. In Proceedings of the 20th International Conference on Computational Linguistics, 841 at the 28th international conference on Human factors in computing systems, ACM.

  • Goldberg, L. R., Johnson, L. A., Eber, H. W., Hogan, R., Ashton, M. C., Cloninger, C. R., et al. (2006). The international personality item pool and the future of public-domain personality measures. Journal of Research in Personality, 40, 84–96.

    Google Scholar 

  • Golder, S. A., & Macy, M. W. (2011). Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures. Science, 30, 1878–1881.

    Article  Google Scholar 

  • Jordan, A. H., Monin, B., Dweck, C. S., Lovett, B. J., John, O. P., & Gross, J. J. (2010). Misery has more company than people think: Underestimating the prevalence of others’ negative emotions. Personality and Social Psychology Bulletin, 37(1), 120–135.

    Google Scholar 

  • Kramer, A. (2010). An unobtrusive behavioral model ofGross National Happiness”. Paper presented at the 28th international conference on human factors in computing systems, ACM.

  • McAllister, F. (2005). Well-being concepts and challenges, Sustainable Development Research Network Discussion paper, December, London. Available at: http://www.sd-research.org.uk/wp-content/uploads/finalwellbeingpolicybriefing.pdf.

  • Miller, G. (2011). Social scientists wade into the tweet stream. Science, 30, 1814–1815.

    Article  Google Scholar 

  • Mishne, G. & de Rijke, M. (2006). Capturing global mood levels using blog posts. In AAAI 2006 spring symposium on computational approaches to analysing weblogs (AAAICAAW 2006).

  • Mullen, T., & Malouf, R. (2006) A preliminary investigation into sentiment analysis of informal political discourse. In Proceedings of the AAAI symposium on computational approaches to analyzing weblogs, 159–162.

  • Nasukawa, T., & Yi, J. (2003). Sentiment analysis: Capturing favorability using natural language processing. In Proceedings of the 2nd international conference on knowledge capture. Florida, USA, 70–77.

  • Pang, B., & Lee, L. (2004). A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts. In: Proceedings of the annual meeting on association for computational linguistics (ACL), 271–278.

  • Pavot, W., & Diener, E. (2009). Review of the satisfaction with life scale assessing well-being: The collected works of Ed Diener. 101–117.

  • Pennebaker, J. W., Chung, C. K., Ireland, M., Gonzales, A., & Booth, R. J. (2007). The development and psychological properties of LIWC 2007. 1–22. Retrieved from Linguistic Inquiry and Word Count website http://www.liwc.net/LIWC2007LanguageManual.pdf.

  • Pennock, M. (2009). Measuring the progress of communities: Applying the Gross National Happiness Framework. Measuring the Progress of Societies, 2009, 9–10.

    Google Scholar 

  • Pennock, M., & Ura, K. (2011). Gross national happiness as a framework for health impact assessment. Environmental Impact Assessment Review, 31(1), 61–65. doi:10.1016/j.eiar.2010.04.003.

    Article  Google Scholar 

  • Schimmack, U., Diener, E., & Oishi, S. (2002). Life-satisfaction is a momentary judgment and a stable personality characteristic: The use of chronically accessible and stable sources. Journal of Personality, 70(3), 345–384.

    Article  Google Scholar 

  • Schwarz, N., & Strack, F. (2003). Reports of subjective well-being: Judgmental processes and their methodological implications. In D. Kahneman, E. Diener, & N. Schwarz (Eds.), Well-being: The foundations of hedonic psychology (pp. 61–84). New York: Russell Sage Foundation.

    Google Scholar 

  • Stillwell, D. J. & Kosinski, M. (2011). myPersonality Research Wiki. myPersonality Project. Retrieved June, 2011, from http://mypersonality.org/wiki.

  • Tausczik, Y. R., & Pennebaker, J. W. (2010). The psychological meaning of words: LIWC and computerized text analysis methods. Journal of Language and Social Psychology, 29(1), 24–54.

    Google Scholar 

  • Testing LIWC Online. (2011). from http://liwc.net/liwcresearch07.php.

  • Ura, K. (2008). The GNH Index, from http://www.grossnationalhappiness.com/gnhIndex/gnhIndexVariables.aspx.

  • Veenhoven, R. (1984). Conditions of Happiness. Dordrecht, The Netherlands: Reidel.

    Book  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to D. J. Stillwell.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Wang, N., Kosinski, M., Stillwell, D.J. et al. Can Well-Being be Measured Using Facebook Status Updates? Validation of Facebook’s Gross National Happiness Index. Soc Indic Res 115, 483–491 (2014). https://doi.org/10.1007/s11205-012-9996-9

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11205-012-9996-9

Keywords

Navigation