Abstract
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.
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References
Bates W (2009) Gross national happiness. Asian-Pac Econ Lit 23:1–16
Diener E, Diener M, Diener C (1995) Factors predicting the subjective well-being of nations. J Pers Soc Psychol 69:851–864
Walker SS, Schimmack U (2008) Validity of a happiness implicit association test as a measure of subjective well-being. J Res Pers 42:490–497
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 287–290
James W, Pennebaker CKC, Ireland M, Gonzales A, Booth RJ (2007) The development and psychometric properties of LIWC2007. LIWC.Net, Austin, TX
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 42–47
Sebastiani AEAF (2006) SentiWordNet: a publicly available lexical resource for opinion mining. In: Language resources and evaluation (LREC), pp 417–422
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 16:731–736
Pennock M, Ura K (2011) Gross National happiness as a framework for health impact assessment. Environ Impact Asses 31:61–65
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 965–968
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 53–60
Miller GA (1995) WordNet: a lexical database for English. Commun ACM 38:39–41
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Wang, D., Khiati, A., Sohn, J., Joo, BG., Chung, IJ. (2014). An Improved Method for Measurement of Gross National Happiness Using Social Network Services. In: Huang, YM., Chao, HC., Deng, DJ., Park, J. (eds) Advanced Technologies, Embedded and Multimedia for Human-centric Computing. Lecture Notes in Electrical Engineering, vol 260. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-7262-5_3
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DOI: https://doi.org/10.1007/978-94-007-7262-5_3
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