Measuring Happiness the Big Data Way

Transcription

1 the Big Data Way Clinical and Translational Research Seminar, UVM Peter Dodds, Chris Danforth, Isabel Kloumann, Cathy Bliss, and Kameron Harris. Department of Mathematics & Statistics Center for Complex Systems Vermont Advanced Computing Center University of Vermont 1 of 66

2 Outline 2 of 66

3 Tonight is the on-average coldest night of the year: 100 Avg. max and min Temperature , Burlington VT 100 Avg. max and min Temperature , Central Park, NYC Fahrenheit Fahrenheit Julian Day Julian Day Hibernal Teletherm February 4. Halfway between Winter Solstice and Spring Equinox Bonus: Groundhog Day ( ), Imbolc ( ),... Aesteval Teletherm July 19 (164 days later). 3 of 66

4 The Team: ks to... The People: Kameron Harris Isabel Kloumann Catherine Bliss The Machines: 1400 processors + storage at the Vermont Advanced Computing Center 30 TB of storage in Danforth s office. arris & Sep Kamvar rg 4 of 66

5 : Socrates et al.: eudaimonia [8] Bentham: hedonistic calculus Jefferson:... the pursuit of happiness 5 of 66

6 Early drafts: 6 of 66

7 : Even the odd modern economist likes happiness: by Richard Layard [10] [amazon] ( ) 7 of 66

8 Desiring happiness not just for boffins: Average people routinely report being happy is what they want most in life [10, 11] National indices of well-being: Bhutan France Australia 8 of 66

9 Emotional content So how does one measure 1. happiness? 2. levels of other emotional states? Just ask people how happy they are. Experience sampling [4, 6, 5] (Csikszentmihalyi et al.) Day reconstruction [9] (Kahneman et al.) But self-reporting has drawbacks... relies on memory and self-perception induces misreporting [12] costly 9 of 66

10 Emotional Content: We d like to build an hedonometer : Ideally: Transparent Fast Based on written expression Uses human evaluation An instrument to remotely-sense emotional states and levels, in real time or post hoc. Non-reactive Complementary to self-reported measures Improvable 10 of 66

11 ANEW study words examples valence v 9 love/paradise/triumphant 8 glory/luxury/trophy 7 optimism/pancakes/church 6 engine/paper/street 5 derelict/neurotic/vanity 4 fault/corrupt/lawsuit 3 trauma/hostage/disgusted 2 funeral/rape/suicide frequency ANEW = Affective Norms for English Words [3] 11 of 66

12 Analysing text: Lyrics for Michael Jackson s Billie Jean She was more like a beauty queen from a movie scene. And mother always told me, be careful who you love. And be careful of what you do cause the lie becomes the truth. Billie Jean is not my lover, She s just a girl who claims that I am the one. ANEW words k=1. love 2. mother 3. baby 4. beauty 5. truth 6. people 7. strong 8. young 9. girl 10. movie 11. perfume 12. queen 13. name 14. lie v k f k v text = v Billie Jean v Thriller v Michael Jackson v k f k k f k k = 7.1 = 6.3 = of 66

13 : Texts: 1. Song lyrics ( ) 2. Song titles ( ) 3. State of the Union () Addresses ( ) Sources: hotlyrics.com ( ) freedb.com ( ) American Presidency Project: ( ). 13 of 66

14 : 4. Blog phrases containing I feel..., I am feeling, etc., taken from wefeelfine.org ( ) (API, ) Thanks to... Kameron Harris Isabel Kloumann Catherine Bliss Created by Jonathan Harris & Sep Kamvar 14 of 66

15 wefeelfine.org: 15 of 66

16 wefeelfine.org: 16 of 66

17 wefeelfine.org: 17 of 66

18 : 5. Tweets from twitter.com: 18 of 66

19 Some numbers: Counts Song lyrics Song titles All words 58,610,849 60,867,223 ANEW words 3,477,575 (5.9%) 5,612,708 (9.2%) Individuals 20, ,000 Counts blogs All words 155,667,394 1,796,763 ANEW words 8,581,226 (5.5%) 61,926 (3.5%) Individuals 2,335, Counts All words ANEW words (3.7%) Individuals of 66

20 Most frequent ANEW words: Rank Song lyrics Song titles 1 love (7.37%) love (7.39%) 2 time (4.18%) time (4.19%) 3 baby (2.75%) baby (2.75%) 4 life (2.59%) life (2.60%) 5 heart (2.14%) heart (2.15%) Rank blogs twitter 1 good (4.89%) people (5.49%) good (4.50%) 2 time (4.72%) time (4.09%) love (4.45%) 3 people (3.94%) present (3.45%) time (3.30%) 4 love (3.31%) world (3.10%) people (2.06%) 5 life (3.13%) war (2.98%) home (1.71%) 20 of 66

21 Text: h avg Words with a similar score: Soul/Gospel lyrics [7] 6.9 chocolate (6.88), leisurely (6.88), penthouse (6.81) Pop lyrics [7] 6.7 dream (6.73), honey (6.73), sugar (6.74) Dante s Paradise [1] 6.5 muffin (6.57), rabbit (6.57), smooth (6.58) Tweets, 9/9/ thought (6.39), face (6.39), blond (6.42) to 12/31/2010 Rock lyrics [7] 6.3 church (6.28), tree (6.32), air (6.34) Enron s [2] 6.2 clouds (6.18), alert (6.20), computer (6.24) State of the Union 6.1 grass (6.12), idol (6.12), bottle (6.15) Messages [7] New York Times 6.0 hotel (6.00), tennis (6.02), wonder (6.03) ( ) [14] [7] 5.8 owl (5.80), whistle (5.81), humble (5.86) Dante s Inferno [1] 5.5 glacier (5.50), repentant (5.53), mischief (5.57) Heavy Metal lyrics [7] 5.4 lamp (5.41), elevator (5.44), truck (5.47)

22 Song Lyrics average happiness (valence) mean valence v avg year 23 of 66

23 Song Lyrics average valence of genres: mean valence v avg Gospel/Soul (6.91) 5.5 Pop (6.69) Reggae (6.40) Rock (6.27) 5 Rap/Hip Hop (6.01) Punk (5.61) Metal/Industrial (5.10) year 24 of 66

24 Word Shift Graph: Word number i Per word drop in valence of lyrics from relative to valence of lyrics from : 1 love Key: lonely hate pain baby love life death baby god home truth dead music party home good sex sick Decreases in relatively Increases in relatively fear high valence words high valence words hit hell contribute to drop contribute to increase fall in average valence in average valence sin lost sad hate lonely pain sad burn death trouble lie dead loneliness scared sick devil afraid Increases in relatively Decreases in relatively music low valence words low valence words life contribute to drop contribute to increase god in average valence in average valence trouble loneliness Per word valence shift i 25 of 66

25 Top 16 of 20,000 artists: Rank Artist Valence 1 All-4-One Luther Vandross S Club K Ci & JoJo Perry Como Diana Ross & The Supremes Buddy Holly Faith Evans The Beach Boys Jon B Dru Hill Earth Wind & Fire Ashanti Otis Redding Faith Hill NSync 6.93 (criteria: 50 songs and 1000 ANEW words) 26 of 66

26 Bottom 16 of 20,000 artists: Rank Artist Valence 1 Slayer Misfits Staind Slipknot Darkthrone Death Black Label Society Pig Voivod Fear Factory Iced Earth Simple Plan Machine Head Metallica Dimmu Borgir Mudvayne 5.21 (criteria: 50 songs and 1000 ANEW words) 27 of 66

27 Overall trend average happiness h avg US Election 11/4 US Inauguration 1/ Michael 5.8 9/10 Jackson 9/10 9/10 9/ A S O ND J FMAM J J A S O ND J FMAM J J A S O ND J FMAM J J A S O ND J FMAM J J A S O ND J FMA of 66

28 valence (v) blogger age Average happiness as a function of the age bloggers report they will turn in the year of their posting. 30 of 66

29 Word rank r sick hate stupid sad T ref : born in (h avg =5.96) T comp : 14 years old (h avg =5.55) depressed bored lonely alone mad pain + life r i=1 δh avg,i upset fat dead scared terrible confused hurt loved + fun + happy + love + friend + people + time Text size: T ref T comp Balance: 169 : Per word average happiness shift δh avg,r (%) 31 of 66

30 Word rank r r i=1 δh avg,i T ref : Male (h avg =5.91) T comp : Female (h avg =5.89) hurt hate sad + good alone stupid guilty sick scared lost + music + free + christmas upset baby + loved + happy + heart + death life + family + cold friend + dead love + Text size: T ref T comp Balance: 607 : Per word average happiness shift δh avg,r (%) 32 of 66

31 Presidential happiness: v avg Theodore Roosevelt William Howard Taft Woodrow Wilson Warren G. Harding Calvin Coolidge Herbert Hoover Franklin D. Roosevelt Harry S. Truman Dwight D. Eisenhower John F. Kennedy year Lyndon B. Johnson Richard Nixon Gerald R. Ford Jimmy Carter Ronald Reagan George Bush William J. Clinton George W. Bush 34 of 66

32 living in the now: count fr breakfast lunch dinner hour of day (local time) 36 of 66

33 living in the now: count fr hungry starving food eat hour of day (local time) 37 of 66

34 living in the now: count (%) hour of day (local time) A few words you can t say on television. 38 of 66

35 living in the now: Tweeting the Superbowl ( ) [NY Times] 39 of 66

36 overall time series: average happiness h avg A 12/25 12/24 12/31 11/27 02/14 01/01 10/31 04/12 06/21 06/25 07/04 Friday Saturday 12/25 Sunday 12/31 11/26 02/14 Monday Tuesday 12/24 Wednesday 10/31 01/01 Thursday 04/04 05/09 06/20 07/04 12/25 12/24 11/25 12/31 10/31 Simpson lexical size N S 6 10/01/08 01/01/09 04/01/09 07/01/09 10/01/09 01/01/10 04/01/10 07/01/10 10/01/10 01/01/ B /01/08 01/01/09 04/01/09 07/01/09 10/01/09 01/01/10 04/01/10 07/01/10 10/01/10 01/01/11 ANEW study word count (10 6 ) C 0 10/01/08 01/01/09 04/01/09 07/01/09 10/01/09 01/01/10 04/01/10 07/01/10 10/01/10 01/01/11 date 40 of 66

37 weekly time series: h avg to : 6.3 T W T F S S M T W T F S S M day of week to : 610 N S S M T W T F S S M T W T F S day of week 41 of 66

38 Word rank r r i=1 δh avg,i T ref : Tuesdays (h avg =6.33) T comp : Saturdays (h avg =6.41) bored + free fight alone love + party + fun + happy + christmas + merry + news hate sick office family + game + birthday + house + Balance: home + 41 : +141 movie wedding + bus beach + lost beautiful Text size: T ref T comp Per word average happiness shift δh avg,r (%) 42 of 66

39 daily time series: h avg to : hour of day (local time) 43 of 66

40 Word rank r love r i=1 δh avg,i T ref : 1 pm to 2 pm (h avg =6.35) T comp : 6 am to 7 am (h avg =6.42) bus cold + party cancer + pretty + food news + win + wit good + happy + sleep + bed + free + god + hell birthday + bored sin hate mad hungry hay hit Text size: T ref T comp Balance: 119 : Per word average happiness shift δh avg,r (%) 44 of 66

41 (amb) h avg Happy :)! Tea Party :( Afghanistan Sad 3 09/09/08 12/01/08 03/01/09 06/01/09 09/01/09 date 1 log 10 rel freq /09/08 12/01/08 03/01/09 06/01/09 09/01/09 date 45 of 66

42 Tref: All Tweets (havg=6.41) Tcomp: Tiger Woods (havg=5.84) (amb) h avg A log 10 rel freq Tiger Woods 10/01/09 12/01/09 02/01/10 04/01/10 06/01/10 date 10/01/09 12/01/09 02/01/10 04/01/10 06/01/10 date Word rank r accident crash + love r i=1 δhavg,i scandal news + good alone + happy hospital divorce hurt golfer fire + fun + music + win sick + free sex + car + hate time bored cold movie + Text size: Tref Tcomp Balance: 180 : Per word average happiness shift δhavg,r (%) 46 of 66

43 Tref: All Tweets (havg=6.37) Tcomp: BP (havg=5.46) (amb) h avg B log 10 rel freq BP 01/01/10 03/01/10 05/01/10 07/01/10 date 01/01/10 03/01/10 05/01/10 07/01/10 date Word rank r 1 disaster + love news crisis 5 dead damage criminal toxic + good 10 + happy r i=1 δhavg,i failure pressure destroy cut + free + win hurt angry accident + home crude anger hate Balance: 137 : +37 people ocean Per word average happiness shift δhavg,r (%) Text size: Tref Tcomp 47 of 66

44 13 Word h (amb) avg Word h (amb) avg Total Tweets Total ANEW Total Tweets Total ANEW 1. love ,687,476 (6) 85,269,499 (5) 51. me ,342,098 (4) 88,088,051 (4) 2. happy ,541,968 (13) 32,442,529 (8) 52.? ,333,283 (53) 674,679 (69) 3. win ,981,856 (26) 14,640,728 (20) 53. commute ,126 (94) 90,092 (92) 4. kiss ,697,405 (59) 3,162,330 (48) 54. gay ,727,309 (47) 1,697,177 (57) 5. cash ,279,236 (63) 2,468,496 (51) 55. right ,166,480 (10) 15,850,283 (19) 6. vacation ,501 (67) 1,783,270 (56) 56. school ,264,217 (24) 6,924,193 (34) 7. Christmas ,887,968 (35) 10,645,630 (25) 57. Republican ,773 (86) 188,338 (85) 8. God ,576,364 (25) 17,867,768 (16) 58. they ,442,360 (8) 27,150,189 (11) 9. party ,438,886 (29) 12,090,597 (23) 59. winter ,255,945 (64) 1,217,225 (64) 10. sex ,551,767 (39) 7,087,972 (31) 60. lose ,056,468 (55) 2,091,540 (53) 11. Valentine ,288 (84) 464,914 (75) 61. Jon Stewart ,084 (97) 33,086 (96) 12. family ,014,816 (32) 10,629,361 (26) 62. gas ,022,879 (65) 812,029 (68) 13. sun ,385,348 (52) 4,602,627 (44) 63. no ,129,093 (5) 38,894,616 (6) 14. life ,006,454 (17) 27,770,768 (10) 64. Democrat ,193 (93) 75,450 (93) 15. hope ,833,337 (18) 22,952,366 (13) 65. left ,893,634 (34) 4,611,878 (43) 16. heaven ,878 (71) 1,485,702 (59) 66. Senate ,732 (78) 316,835 (80) 17. :) ,470,483 (20) 6,787,678 (35) 67. election ,184 (75) 375,055 (78) 18. income ,425 (76) 418,161 (77) 68. Sarah Palin ,577 (87) 150,096 (88) 19. friends ,669,719 (27) 7,541,106 (29) 69. Obama ,981,150 (44) 1,998,326 (54) 20. snow ,596,165 (49) 5,011,785 (40) 70. economy ,878 (73) 460,834 (76) 21. :-) ,680,165 (60) 1,102,512 (67) 71. Congress ,510 (79) 279,695 (81) 22. night ,089,505 (12) 17,606,796 (17) 72. drugs ,606 (77) 469,091 (74) 23. vegan ,889 (90) 178,676 (86) 73. Muslim ,300 (88) 146,506 (89) 24. Jesus ,027,720 (56) 1,673,992 (58) 74. George Bush ,341 (98) 23,102 (98) 25. girl ,070,132 (22) 19,886,691 (14) 75. climate ,177 (80) 229,129 (83) 26. USA ,157,172 (54) 1,204,585 (65) 76. Pope ,320 (91) 135,955 (90) 27. you ,276,993 (3) 145,464,084 (2) 77. oil ,377,355 (62) 1,148,990 (66) 28. our ,062,465 (16) 14,437,899 (21) 78. I feel ,173,513 (31) 4,702,352 (42) 29. ;) ,618,940 (48) 1,475,221 (60) 79. Glenn Beck ,991 (92) 101,090 (91) 30. health ,575,543 (50) 4,950,202 (41) 80. Islam ,223 (89) 70,311 (94) 31. tomorrow ,379,637 (21) 8,899,406 (28) 81. :-( ,141 (81) 244,215 (82) 32.! ,463,257 (40) 1,385,072 (62) 82. :( ,907,145 (45) 1,891,225 (55) 33. summer ,998,785 (43) 2,554,459 (50) 83. flu ,403 (68) 639,000 (70) 34. we ,132,934 (7) 34,513,587 (7) 84. rain ,233,464 (41) 5,959,903 (38) 35. today ,588,506 (9) 23,619,518 (12) 85. BP ,167 (74) 326,100 (79) 36. man ,856,341 (14) 29,558,118 (9) 86. mosque ,812 (95) 46,736 (95) 37. woman ,543,036 (51) 5,603,347 (39) 87. dark ,577,553 (61) 3,233,911 (47) 38. Stephen Colbert ,778 (99) 14,697 (99) 88. Lehman Brothers ,500 (100) 4,280 (100) 39. ;-) ,413 (66) 516,171 (73) 89. Goldman Sachs ,703 (96) 30,769 (97) 40. RT ,055,724 (1) 142,219,359 (3) 90. Afghanistan ,519 (83) 172,637 (87) 41. coffee ,800,972 (46) 2,399,867 (52) 91. Iraq ,931 (85) 213,425 (84) 42. church ,812,251 (58) 3,452,171 (45) 92. cold ,670,447 (36) 7,015,518 (32) 43. work ,415,618 (11) 16,191,802 (18) 93. gun ,903 (72) 1,263,217 (63) 44. I ,960,343 (2) 282,865,043 (1) 94. hate ,652,881 (23) 18,158,870 (15) 45. yes ,593,356 (19) 7,499,840 (30) 95. hell ,266,162 (30) 11,056,735 (24) 46. them ,352,295 (15) 14,398,889 (22) 96. sick ,576,058 (37) 6,783,395 (36) 47. hot ,122,144 (28) 6,286,163 (37) 97. sad ,563,745 (38) 6,951,686 (33) 48. boy ,933,333 (33) 9,670,512 (27) 98. war ,955,901 (57) 3,417,588 (46) 49. yesterday ,077,761 (42) 2,852,623 (49) 99. depressed ,872 (82) 541,394 (72) 50. Michael Jackson ,979 (70) 571,442 (71) 100. headache ,600 (69) 1,446,064 (61)

45 location: 49 of 66

46 location: Word rank r r i=1 δhavg,i T ref : NY (h avg =6.32) T comp : CA (h avg =6.38) + wit + snow time rain + music + sex bomb ambulance fire mad fun + beach + home + hell dead free + hate car + cold fall bus cut square hit accident Text size: T ref T comp Balance: 79 : Per word average happiness shift δh avg,r (%) 50 of 66

47 popularity based on follower count: /09/08 06/30/ /09/08 06/30/09 # ANEW # Words (h avg ) Ambient Diversity (N S (amb) ) Background: Follower Count Follower Count Dunbar s number of 66

48 popularity based on follower count: Word rank r T ref : 10 2 followers (h avg =6.29) T comp : 10 3 followers (h avg =6.44) + home + bed + sleep + god + christmas news r i=1 δhavg,i failure free + hate sick bored good + people + hell stupid love + cold social + success + sad money + Balance: 93 : +193 headache + + lost hungry war Text size: T ref T comp of 66

49 inters: Decay in happiness correlation in social network. ρ = Spearman s correlation coefficient. 53 of 66

50 : valence word frequency valence st. dev. rank rank 1 happiness love happy laughed vacation laugh laughing enjoyed celebration excellent congratulations joy successful win won smile rainbow pleasure winning success of 66

51 : Table 1 continued valence word frequency valence st. dev. rank frequency 4975 failed cruel war jail kills die killing arrested deaths torture death died kill killed cancer terrorism murder rape suicide terrorist of 66

52 Variable words: Sorted by standard deviations! std dev word frequency valence st. dev. rank frequency 1 fucking fuckin fucked fuck pussy porn beer aids crazy drunk drama alcohol prayer chilling tobacco beef rainy raining obama walmart palin christ haiti naked of 66

53 Positive bias in the English language: N h avg 57 of 66

54 Downloaded from on January 1 Frequency (log) Frequency RESEARCH ARTICLE they were first invented ( , , and ) (7). We tracked the frequency of each invention in the nth year after it was invented as compared to its maximum value and plotted the median of these rescaled trajectories for each cohort. The inventions from the earliest cohort ( ) took over 66 years from invention contrast, 1973 declined to half its peak by x , a lag of only 10 years. We are forgetting our past faster with each passing year (Fig. 3A). 5 We were curious whether our increasing tendency to forget the old was accompanied by 0more rapid assimilation of the new (21). We divided a list of 147 inventions into time-resolved cohorts based on the 40-year interval in which F ian frequency Frequency (log) E (gray lines; median, thick dark gray line). Five examples are highlighted Half life : 73 yrs :4 yrs phase (73 years, red line). Inset: The doubling time and half-life over time. (F) The median trajectory of the 25 most famous personalities born between 1800 and 1920 in various careers. me x10-5 Frequency g ti me :4 yrs : 73 yrs 5 0 F 3. Cultural turnover is accelerating. (A) We forget: frequency of 1883 Fig. D 1910 (green), and 1950 (red). Inset: We forget faster. The half-life (blue), of the curves (gray dots) is getting shorter (gray line: moving average). (B) Cultural adoption is quicker. Median trajectory for three cohorts of inventions from three different time periods ( , blue; , green; , red). Inset: The telephone (green; date of invention, green arrow) and radio (blue; date of invention, blue arrow). (C) Fame of various personalities born between 1920 and (D) Frequency of the 50 most famous people born in (E) The median trajectory of the 1865 cohort is characterized by four ( ) 14 JANUARY 2011 VOL 331 SCIENCE parameters: (i) initial age of celebrity (34 years old, tick mark); (ii) doubling time of the subsequent rise to fame (4 years, blue line); (iii) age of peak celebrity Google ngram viewer (70 years after birth,books tick mark), and (iv) half-life of the post-peak forgetting ( ) g ti Half life SCIENCE F Median frequency Downloaded from on January 14, 2011 Year of invention blin E B D Dou Frequency 天安 Frequency Median frequency Frequency Frequency (log) Quantitative analysis of culture using millions of digitized books by Michel et al., Science, 2011 [13] frequency (log) 1883 alf-life ultural m three 1920, radio s born born in Frequency Culturomics: Median frequency Frequency Frequency Median frequency (log) Frequency (% of peak value) Downloaded from on January 14, 2011 Median frequenc (% of peak value) ared to English (blue). (B) ion of Leon Trotsky (blue), Zinoviev (green), and Lev enter a regime marked by slower forgetting: v (red) in Russian texts, Collective memory has both a short-term and a eworthy events indicated: long-term component. assassination (blue arrow), But executed there have been changes. The amplitude and Kamenev of the Purge plots is(red rising every year: Precise dates are ow), the Great increasingly There is also a greater fo), and perestroika (graycommon. arthetiananpresent. For instance, 1880 declined The 1976 cus and on 1989 to half its peak value in 1912, a lag of 32 years. In uare incidents both led to discussion in English texts own on the right). Response 989 incident largely aba is scale hinese texts (blue, shown C D ft), suggesting government ip. (D) While the Hollyen were blacklisted (red t) from U.S. movie studios, me declined (median: thick ). None of them were creda film until 1960 s (aptly Exodus. (E) Artists and writrious disciplines were supby the Nazi regime (red ). In contrast, the Nazis themhick red line) exhibited a ame peak during the war ) Distribution of suppresces for both English (blue) man (red) forfthe period from E 945. ThreeC victims of Nazi ion are highlighted at left ows). Inset: Calculation of pression index for Henri (gray lines; median, thick dark gray line). Five ex (E) The median trajectory of the 1865 cohort is parameters: (i) initial age of celebrity (34 years old, time of the subsequent rise to fame (4 years, blue line); (70 years after birth, tick mark), and (iv) half-life of t phase (73 years, red line). Inset: The doubling time (F) The median trajectory of the 25 most famous per 1800 and 1920 in various careers. VOL JANUARY of 66

55 What matters and what s measurable: 59 of 66

56 Economics, Schmeconomics Alan Greenspan (September 18, 2007): I ve been dealing with these big mathematical models of forecasting the economy... If I could figure out a way to determine whether or not people are more fearful or changing to more euphoric, I don t need any of this other stuff. I could forecast the economy better than any way I know of 66

57 Economics, Schmeconomics Greenspan continues: The trouble is that we can t figure that out. I ve been in the forecasting business for 50 years. I m no better than I ever was, and nobody else is. Forecasting 50 years ago was as good or as bad as it is today. And the reason is that human nature hasn t changed. We can t improve ourselves. Jon Stewart: You just bummed out of me. wildbluffmedia.com From the Daily Show ( ) (September 18, 2007) The full inteview is here ( ). 61 of 66

58 For more... PSD, KDH, IMK, CAB, and CMD Temporal patterns of happiness and information in a global social network: Hedonometrics and. ( ) P. S. Dodds and C. M. Danforth the of Large-Scale Written Expression:,, and Presidents. [7] Journal of Studies, pdodds/research/ ( ) Does a Nation s Mood Lurk in Its and? by Benedict Carey New York Times, August ( ) ( )

59 I [1] [2] [3] M. Bradley and P. Lang. Affective norms for english words (anew): Stimuli, instruction manual and affective ratings. Technical report c-1, University of Florida, Gainesville, FL, pdf ( ) [4] T. Conner Christensen, L. Feldman Barrett, E. Bliss-Moreau, K. Lebo, and C. Kaschub. A practical guide to experience-sampling procedures. Journal of Studies, 4:53 78, of 66

60 II [5] M. Csikszentmihalyi. Flow. Harper & Row, New York, [6] M. Csikszentmihalyi, R. Larson, and S. Prescott. The ecology of adolescent activity and experience. Journal of Youth and Adolescence, 6: , [7] P. S. Dodds and C. M. Danforth. the happiness of large-scale written expression:, blogs, and presidents. Journal of Studies, doi: /s pdf ( ) [8] W. T. Jones. The Classical Mind. Harcourt, Brace, Jovanovich, New York, of 66

61 III [9] D. Kahneman, A. B. Krueger, D. A. Schkade, N. Schwarz, and A. A. Stone. A survey method for characterizing daily life experience: The day reconstruction method. Science, 306(5702): , pdf ( ) [10] R. Layard.. The Penguin Press, London, [11] S. Lyubomirsky. The How of. The Penguin Press, New York, [12] C. Martinelli and S. W. Parker. Deception and misreporting in a social program. forthcoming in Journal of the European Economic Association, pdf ( ) 65 of 66

62 IV [13] J.-B. Michel, Y. K. Shen, A. P. Aiden, A. Veres, M. K. Gray, The Google Books Team, J. P. Pickett, D. Hoiberg, D. Clancy, P. Norvig, J. Orwant, S. Pinker, M. A. Nowak, and E. A. Lieberman. Quantitative analysis of culture using millions of digitized books. Science Magazine, 331: , pdf ( ) [14] E. Sandhaus. The New York Times Annotated Corpus. Linguistic Data Consortium, Philadelphia, of 66