Psychological Language on Twitter Predicts County-Level Heart Disease Mortality

Psychological Science

Volumn 26, Issue 2, 2015, Pages 159-169

  Eichstaedt, Johannes C ^a   Schwartz, Hansen Andrew ^a,b   Kern, Margaret L ^a,c   Park, Gregory ^a   Labarthe, Darwin R ^d   Merchant, Raina M ^a   Jha, Sneha ^b   Agrawal, Megha ^b   Dziurzynski, Lukasz A ^a   Sap, Maarten ^a   Weeg, Christopher ^a   Larson, Emily E ^a   Ungar, Lyle H ^a,b   Seligman, Martin E P ^a  

^a UNIVERSITY OF PENNSYLVANIA   (United States)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c UNIVERSITY OF MELBOURNE   (Australia)

^d NORTHWESTERN UNIVERSITY   (United States)

Author keywords

big data; emotions; heart disease; language; open data; open materials; risk factors; social media; well being

Indexed keywords

CORONARY ARTERY DISEASE; CROSS-SECTIONAL STUDY; EMOTION; EPIDEMIOLOGY; FEMALE; HUMAN; INFORMATION PROCESSING; LANGUAGE; MALE; MORTALITY; PSYCHOLOGICAL MODEL; PSYCHOLOGY; REGRESSION ANALYSIS; RISK FACTOR; SOCIAL MEDIA; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; UNITED STATES;

CORONARY ARTERY DISEASE; CROSS-SECTIONAL STUDIES; DATA COLLECTION; EMOTIONS; FEMALE; HUMANS; LANGUAGE; MALE; MODELS, PSYCHOLOGICAL; MODELS, STATISTICAL; REGRESSION ANALYSIS; RISK FACTORS; SOCIAL MEDIA; UNITED STATES;

EID: 84922758277     PISSN: 09567976     EISSN: 14679280     Source Type: Journal    
DOI: 10.1177/0956797614557867     Document Type: Article

References (52)

1. Auchincloss A. H.,Gebreab S. Y.,Mair C.,Diez Roux A. V.A review of spatial methods in epidemiology, 2000–2010.Annual Review of Public Health. 2012;33:107-122
2. Boehm J. K.,Kubzansky L. D.The heart’s content: The association between positive psychological well-being and cardiovascular health.Psychological Bulletin. 2012;138:655-691
3. Boehm J. K.,Kubzansky L. D.Cardiovascular behavioral medicine. Kop W.Katzel L.Waldstein S., ed. New York, NY: Springer; in press:
4. Centers for Disease Control and Prevention. (2009). Behavioral Risk Factor Surveillance System annual survey data. Retrieved from http://www.cdc.gov/brfss/annual_data/annual_2009.htm
5. Centers for Disease Control and Prevention. (2010a). Behavioral Risk Factor Surveillance System annual survey data. Retrieved from http://www.cdc.gov/brfss/annual_data/annual_2010.htm
6. Centers for Disease Control and Prevention. (2010b). Underlying cause of death 1999-2010. CDC WONDER online database [Data set]. Retrieved from http://wonder.cdc.gov/ucd-icd10.html
7. Chaix B.,Merlo J.,Evans D.,Leal C.,Havard S.Neighbourhoods in eco-epidemiologic research: Delimiting personal exposure areas. A response to Riva, Gauvin, Apparicio and Brodeur.Social Science & Medicine. 2009;69:1306-1310
8. ChewC.EysenbachG. (2010). Pandemics in the age of Twitter: Content analysis of tweets during the 2009 H1N1 outbreak. PLoS ONE, 5(11), Article e14118. Retrieved from http://www.plosone.org/article/info:doi/10.1371/journal.pone.0014118
9. Chida Y.,Steptoe A.Positive psychological well-being and mortality: A quantitative review of prospective observational studies.Psychosomatic Medicine. 2008;70:741-756
10. Chida Y.,Steptoe A.The association of anger and hostility with future coronary heart disease: A meta-analytic view of prospective evidence.Journal of the American College of Cardiology. 2009;53:936-946
11. Cohen D. A.,Farley T. A.,Mason K.Why is poverty unhealthy? Social and physical mediators.Social Science & Medicine. 2003;57:1631-1641
12. De Choudhury M.,Counts S.,Horvitz E.Social media as a measurement tool of depression in populations.WebSci ’13: Proceedings of the 5th Annual ACM Web Science Conference; 2013; 2013. 47.
13. de Quincey E.,Kostkova P.Early warning and outbreak detection using social networking websites: The potential of Twitter.Electronic Healthcare: Second International ICST Conference, eHealth 2009; 2009Istanbul, Turkey; 2009. 21.
14. Diez Roux A. V.,Mair C.Neighborhoods and health.Annals of the New York Academy of Sciences. 2010;1186:125-145
15. EysenbachG. (2009). Infodemiology and infoveillance: Framework for an emerging set of public health informatics methods to analyze search, communication and publication behavior on the Internet. Journal of Medical Internet Research, 11(1), Article e11. Retrieved from http://www.jmir.org/2009/1/e11/.
16. Ford E. S.,Capewell S.Proportion of the decline in cardiovascular mortality disease due to prevention versus treatments: Public health versus clinical care.Annual Review of Public Health. 2011;32:5-22
17. FoxS.ZickurhK.SmithA. (2009). Twitter and status updating, fall 2009. Retrieved from Pew Research Internet Project Web site: http://www.pewinternet.org/2009/10/21/twitter-and-status-updating-fall-2009
18. Fredrickson B. L.,Mancuso R. A.,Branigan C.,Tugade M. M.The undoing effects of positive emotions.Motivation and Emotion. 2000;24:237-258
19. Friedman H. S.,Kern M. L.Personality, well-being, and health.Annual Review of Psychology. 2014;65:719-742
20. Ginsberg J.,Mohebbi M. H.,Patel R. S.,Brammer L.,Smolinski M. S.,Brilliant L.Detecting influenza epidemics using search engine query data.Nature. 2009;457:1012-1014
21. Grimmer J.,Stewart B. M.Text as data: The promise and pitfalls of automatic content analysis methods for political texts.Political Analysis. 2013;21:267-297
22. Howell R.,Kern M. L.,Lyubomirsky S.Health benefits: Meta-analytically determining the impact of well-being on objective health outcomes.Health Psychology Review. 2007;1:83-136
23. Labarthe D. R.Epidemiology and prevention of cardiovascular disease: A global challenge. Sudbury, MA: Jones & Bartlett; 2010:
24. Lett H. S.,Blumenthal J. A.,Babyak M. A.,Sherwood A.,Strauman T.,Robins C.,Newman M. F.Depression as a risk factor for coronary artery disease: Evidence, mechanisms, and treatment.Psychosomatic Medicine. 2004;66:305-315
25. Leyland A. H.Socioeconomic gradients in the prevalence of cardiovascular disease in Scotland: The roles of composition and context.Journal of Epidemiology & Community Health. 2005;59:799-803
26. Lloyd-Jones D. M.,Hong Y.,Labarthe D.,Mozaffarian D.,Appel L. J.,Van Horn L.,.. Rosamond W. D.Defining and setting national goals for cardiovascular health promotion and disease reduction: The American Heart Association’s strategic Impact Goal through 2020 and beyond.Circulation. 2010;121:585-613
27. Lochner K. A.,Kawachi I.,Brennan R. T.,Buka S. L.Social capital and neighborhood mortality rates in Chicago.Social Science & Medicine. 2003;56:1797-1805
28. Menezes A. R.,Lavie C. J.,Milani R. V.,O’Keefe J.,Lavie T. J.Psychological risk factors and cardiovascular disease: Is it all in your head?.Postgraduate Medicine. 2011;123:165-176
29. MisloveA.LehmannS.AhnY.-Y.OnnelaJ. P.RosenquistJ. N. (2011). Understanding the demographics of Twitter users. In Proceedings of the 5th International AAAI Conference on Weblogs and Social Media (pp. 554–557). Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2816/3234
30. PaulM. J.DredzeM. (2011a). A model for mining public health topics from Twitter. Retrieved from the Johns Hopkins University Web site: http://www.cs.jhu.edu/~mpaul/files/2011.tech.twitter_health.pdf
31. PaulM. J.DredzeM. (2011b). You are what you tweet: Analyzing Twitter for public health. In Proceedings of the 5th International AAAI Conference on Weblogs and Social Media (pp. 265–272). Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM11/paper/view/2880/3264
32. Pennebaker J. W.,Chung C. K.,Ireland M.,Gonzales A.,Booth R. J.The development and psychometric properties of LIWC2007. Austin, TX: LIWC.net; 2007:
33. Pennebaker J. W.,Mehl M. R.,Niederhoffer K. G.Psychological aspects of natural language use: Our words, our selves.Annual Review of Psychology. 2003;54:547-577
34. Pierce J. R.,Denison A. V.Handbook of disease burdens and quality of life measures. Preedy V. R.Watson R. R., ed. New York, NY: Springer; 2010:329-344.
35. Pressman S. D.,Cohen S.Does positive affect influence health?.Psychological Bulletin. 2005;131:925-971
36. Riva M.,Gauvin L.,Barnett T. A.Toward the next generation of research into small area effects on health: A synthesis of multilevel investigations published since.Journal of Epidemiology & Community Health. 2007 1998;61:853-861
37. Roest A. M.,Martens E. J.,de Jonge P.,Denollet J.Anxiety and risk of incident coronary heart disease: A meta-analysis.Journal of the American College of Cardiology. 2010;56:38-46
38. Rosenthal R.,DiMatteo M. R.Meta-analysis: Recent developments in quantitative methods for literature reviews.Annual Review of Psychology. 2001;52:59-82
39. Rost M.,Barkhuus L.,Cramer H.,Brown B..Paper presented at the 16th ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW 2013); 2013San Antonio, TX; 2013.
40. Rowe J. W.,Kahn R. L.Human aging: Usual and successful.Science. 1987;237:143-149
41. Rugulies R.Depression as a predictor for coronary heart disease: A review and meta-analysis.American Journal of Preventive Medicine. 2002;23:51-61
42. Salathé M.,Freifeld C. C.,Mekaru S. R.,Tomasulo A. F.,Brownstein J. S.Influenza A (H7N9) and the importance of digital epidemiology.New England Journal of Medicine. 2013;369:401-404
43. SchwartzH. A.EichstaedtJ. C.KernM. L.DziurzynskiL.LucasR. E.AgrawalM.. UngarL. H. (2013). Characterizing geographic variation in well-being using tweets. In Proceedings of the 7th International AAAI Conference on Weblogs and Social Media (pp. 583–591). Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM13/paper/view/6138/6398.
44. SchwartzH. A.EichstaedtJ. C.KernM. L.DziurzynskiL.RamonesS. M.AgrawalM.. UngarL. H. (2013). Personality, gender, and age in the language of social media: The open-vocabulary approach. PLoS ONE, 8(9), Article e73791. Retrieved from http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073791
45. Seifter A.,Schwarzwalder A.,Geis K.,Aucott J.The utility of “Google Trends” for epidemiological research: Lyme disease as an example.Geospatial Health. 2010;4:135-137
46. St LouisC.ZorluG. (2012). Can Twitter predict disease outbreaks?British Medical Journal, 344, Article e2353. Retrieved from http://www.bmj.com/content/344/bmj.e2353
47. Stone P. J.,Dunphy D. C.,Smith M. S.,Ogilvie D. M.The general inquirer: A computer approach to content analysis. Cambridge, MA: MIT Press; 1966:
48. Tay L.,Tan K.,Diener E.,Gonzalez E.Social relations, health behaviors, and health outcomes: A survey and synthesis.Applied Psychology: Health and Well-Being. 2013;5:28-78
49. U.S. Census Bureau. (2009). Selected social characteristics in the United States: 2009. American Community Survey 1-year estimates. Retrieved from http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_09_1YR_DP2&prodType=table
50. U.S. Census Bureau. (2010). Profile of general population and housing characteristics: 2010 demographic profile data. Retrieved from http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=DEC_10_DP_DPDP1&prodType=table
51. World Health Organization. (1992). Atherosclerotic heart disease. In International statistical classification of diseases and related health problems (10th ed.). Retrieved from http://apps.who.int/classifications/icd10/browse/2010/en#/I25.1
52. World Health Organization. (2011). Global status report on noncommunicable diseases 2010. Description of the global burden of NCDs, their risk factors and determinants. Retrieved from http://www.who.int/nmh/publications/ncd_report2010/en/