An Improved Method for Measurement of Gross National Happiness Using Social Network Services

  • Dongsheng Wang
  • Abdelilah Khiati
  • Jongsoo Sohn
  • Bok-Gyu Joo
  • In-Jeong Chung
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 260)


Studies on the measurement of happiness have been utilized in a variety of areas; in particular, it has played an important role in the measurement of society stability. As the number of users of Social Network Services (SNSs) increase, efforts are being made to measure human well-being by analyzing user messages in SNSs. Most previous works mainly counted positive and negative words; they did not consider the grammar and emotion. In this paper, we reorganize the mechanism to harness the advantages of (a) Part-Of-Speech (POS) tagging for grammatical analysis, and (b) the SentiWordNet lexicon for the assignment of sentiment scores for emotion degree. We suggest a modified formula for calculating the Gross National Happiness (GNH). To verify the method, we gather a real-world dataset from 405,700 Twitter users, measure the GNH, and compare it with the Gallup well-being release. We demonstrate that the method has more precise computation ability for GNH.


Social network service (SNS) Happiness Well-being Gross national happiness (GNH) 


  1. 1.
    Bates W (2009) Gross national happiness. Asian-Pac Econ Lit 23:1–16CrossRefGoogle Scholar
  2. 2.
    Diener E, Diener M, Diener C (1995) Factors predicting the subjective well-being of nations. J Pers Soc Psychol 69:851–864CrossRefGoogle Scholar
  3. 3.
    Walker SS, Schimmack U (2008) Validity of a happiness implicit association test as a measure of subjective well-being. J Res Pers 42:490–497CrossRefGoogle Scholar
  4. 4.
    Kramer ADI (2010) An unobtrusive behavioral model of “gross national happiness.” In: 28th international conference on human factors in computing systems, ACM, Atlanta, Georgia, USA, pp 287–290Google Scholar
  5. 5.
    James W, Pennebaker CKC, Ireland M, Gonzales A, Booth RJ (2007) The development and psychometric properties of LIWC2007. LIWC.Net, Austin, TXGoogle Scholar
  6. 6.
    Gimpel K, Schneider N, O’Connor B, Das D, Mills D, Eisenstein J, Heilman M, Yogatama D, Flanigan J, Smith NA (2011) Part-of-speech tagging for Twitter: annotation, features, and experiments. In: 49th annual meeting of the association for computational linguistics: human language technologies: short papers. vol 2. Association for Computational Linguistics, Portland, Oregon, pp 42–47Google Scholar
  7. 7.
    Sebastiani AEAF (2006) SentiWordNet: a publicly available lexical resource for opinion mining. In: Language resources and evaluation (LREC), pp 417–422Google Scholar
  8. 8.
    Tobgay T, Dorji T, Pelzom D, Gibbons RV (2011) Progress and delivery of health care in Bhutan, the land of the thunder dragon and gross National happiness. Trop Med Int Health 16:731–736CrossRefGoogle Scholar
  9. 9.
    Pennock M, Ura K (2011) Gross National happiness as a framework for health impact assessment. Environ Impact Asses 31:61–65CrossRefGoogle Scholar
  10. 10.
    Quercia D, Ellis J, Capra L, Crowcroft J (2012) Tracking “gross community happiness” from Tweets. In: ACM 2012 conference on computer supported cooperative work. ACM, Seattle, Washington, USA, pp 965–968Google Scholar
  11. 11.
    Brew A, Greene D, Archambault D, Cunningham P (2011) Deriving insights from National happiness indices. In: 2011 IEEE 11th international conference on data mining workshops. IEEE Computer Society, pp 53–60Google Scholar
  12. 12.
    Miller GA (1995) WordNet: a lexical database for English. Commun ACM 38:39–41CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Dongsheng Wang
    • 1
  • Abdelilah Khiati
    • 1
  • Jongsoo Sohn
    • 2
  • Bok-Gyu Joo
    • 3
  • In-Jeong Chung
    • 1
  1. 1.Department of Computer and Information ScienceKorea UniversitySeoulKorea
  2. 2.Service Strategy Team, Visual Display, Samsung ElectronicsSeoulKorea
  3. 3.Department of Computer and Information CommunicationsHong-Ik UniversitySeoulKorea

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