Getting the word out: Neural correlates of enthusiastic message propagation

Frontiers in Human Neuroscience

Volumn , Issue OCTOBER 2012, 2012, Pages

  Falk, Emily B ^a,b   O'Donnell, Matthew B ^b   Lieberman, Matthew D ^c  

^a UNIVERSITY OF MICHIGAN   (United States)

^b University's Inst for Social Res   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Enthusiasm; FMRI; Information diffusion; Natural Language Processing; Self related processing; Sentiment analysis; Social cognition

Indexed keywords

ADULT; ASSOCIATION; BEHAVIOR; CLASSIFIER; COGNITION; CORPUS STRIATUM; ENTHUSIASM; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; HUMAN EXPERIMENT; INFERIOR PARIETAL LOBULE; INTERPERSONAL COMMUNICATION; INTERVIEW; LINGUISTICS; MALE; MEDIAL PREFRONTAL CORTEX; NATURAL LANGUAGE PROCESSING; NORMAL HUMAN; POSTERIOR CINGULATE; PRECUNEUS; PREFRONTAL CORTEX; PREMOTOR CORTEX; REVIEW; TEMPORAL LOBE;

EID: 84933670819     PISSN: 16625161     EISSN: None     Source Type: Journal    
DOI: 10.3389/fnhum.2012.00313     Document Type: Review

References (70)

1. Albarracin, D., Johnson, B.T., and Zanna, M.P. (eds.). (2005). The Handbook of Attitudes. Mahwah, NJ: Lawrence Erlbaum.
2. Ambady, N., and Rosenthal, R. (1992). Thin slices of expressive behavior as predictors of interpersonal consequences: A meta-analysis. Psychological Bulletin 111, 256-274.
3. Armitage, C.J., and Conner, M. (2001). Efficacy of the Theory of Planned Behavior: A metaanalytic review. British Journal of Social Psychology 40, 471-499.
4. Bakshy, E., Hofman, J.M., Mason, W.A., and Watts, D.J. (Year). Everyone's an Influencer: Quantifying Influence on Twitter, in: WSDM).
5. Berger, J., and Milkman, K.L. (2012). What Makes Online Content Viral? Journal of Marketing Research 1--46.
6. Berns, G.S., Capra, C.M., Moore, S., and Noussair, C. (2010). Neural mechanisms of the influence of popularity on adolescent ratings of music. Neuroimage 49, 2687-2696.
7. Berns, G.S., and Moore, S.E. (2012). A neural predictor of cultural popularity. Journal of Consumer Psychology 22, 154-160.
8. Bird, S., Klein, E., and Loper, E. (2009). Natural Language Processing with Python. O'Reilly Media.
9. Bliese, P. (2008). multilevel: Multilevel Functions.).
10. Brown, J., Broderick, A.J., and Lee, N. (2007). Word of mouth communication within online communities: Conceptualizing the online social network. Journal of Interactive Marketing 21, 2-20.
11. Cabeza, R., and Nyberg, L. (2000). Neural bases of learning and memory: functional neuroimaging evidence. Curr Opin Neurol 13, 415-421.
12. Campbell-Meiklejohn, D.K., Bach, D.R., Roepstorff, A., Dolan, R.J., and Frith, C.D. (2010). How the opinion of others affects our valuation of objects. Current Biology 20, 1165-1170.
13. Chaiken, S., Liberman, A., and Eagly, A.H. (1989). Heuristic and systematic information processing within and beyond the persuasion context, in Unintended thought, eds. J. Uleman & J.A. Bargh. (New York, NY: Guilford Press), 212-252.
14. Christakis, N.A., and Fowler, J.H. (2007). The spread of obesity in a large social network over 32 years. N Engl J Med 357, 370-379.
15. Chua, H.F., Ho, S.S., Jasinska, A.J., Polk, T.A., Welsh, R.C., Liberzon, I., and Strecher, V.J. (2011). Self-related neural response to tailored smoking-cessation messages predicts quitting. Nat Neurosci 14, 426-427.
16. Eagly, A.H., and Chaiken, S. (1993). The psychology of attitudes. Orlando, FL: Harcourt Brace Jovanovich College Publishers.
17. Eagly, A.H., and Chaiken, S. (2005). Attitude research in the 21st century: The current state knowledge. Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.
18. Eisenstein, J., O'connor, B., Smith, N.A., and Xing, E.P. (2010). A latent variable model for geographic lexical variation, in: Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing. (Cambridge, Massachusetts: Association for Computational Linguistics).
19. Falk, E.B., Berkman, E.T., and Lieberman, M.D. (2012). From neural responses to population behavior: Neural focus group predicts population level media effects. Psychological Science
20. Falk, E.B., Berkman, E.T., Mann, T., Harrison, B., and Lieberman, M.D. (2010). Predicti1 ng persuasion-induced behavior change from the brain. Journal of Neuroscience 30, 8421-8424.
21. Falk, E.B., Berkman, E.T., Whalen, D., and Lieberman, M.D. (2011). Neural activity during health messaging predicts reductions in smoking above and beyond self-report. Health Psychol 30, 177-185.
22. Falk, E.B., Morelli, S.A., Welborn, B.L., Dambacher, K., and Lieberman, M.D. (under revision). Creating buzz: the neural correlates of effective message propagation. Psychological Science Fishbein, M., and Ajzen, I. (1975). Belief, attitude, intention, and behavior: An introduction theory and research. Reading, MA: Addison-Wesley.
23. Fishbein, M., Triandis, H.C., Kanfer, F.H., Becker, M., Middlestadt, S.E., and Eichler, A. (2001). Factors influencing behavior and behavior change, in Handbook of health psychology eds. A. Baum, T.A. Revenson & J.E. Singer. (Mahwah, NJ: Lawrence Erlbaum Associates), 3-16.
24. Fowler, J.H., and Christakis, N.A. (2008). Dynamic spread of happiness in a large social network: longitudinal analysis over 20 years in the Framingham Heart Study. BMJ 337, a2338-a2338.
25. Fowler, J.H., and Christakis, N.A. (2010). Cooperative behavior cascades in human social networks. Proc Natl Acad Sci U S A 107, 5334-5338.
26. Go, A., Bhayani, R., and Huang, L. (2009). Twitter Sentiment Classification using Distant Supervision, in: Processing.).
27. Haber, S.N., and Knutson, B. (2010). The reward circuit: linking primate anatomy and nd human imaging. Neuropsychopharmacology 35, 4-26.
28. Hasson, U., Nir, Y., Levy, I., Fuhrmann, G., and Malach, R. (2004). Intersubject synchronization of cortical activity during natural vision. Science 303, 1634-1640.
29. Hofstadter, D.R. (1985). Metamagical themas: questing for the essence of mind and pattern. New York: Basic Books.
30. Katz, E. (1957). The two-step flow of communication: an up-to-date report of an hypothesis. Public Opinion Quarterly 21, 61-78.
31. Katz, E., and Lazarsfeld, P. (1955). Personal Influence: The Part Played by People in the Flow of Mass Communications. Glencoe, Ill: Free Press.
32. Kim, S.-M., and Hovy, E. (2006). Identifying and analyzing judgment opinions, in: Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics. (New York, New York: Association for Computational Linguistics).
33. Klucharev, V., Hytonen, K., Rijpkema, M., Smidts, A., and Fernandez, G. (2009). Reinforcement learning signal predicts social conformity. Neuron 61, 140-151.
34. Klucharev, V., Munneke, M.A., Smidts, A., and Fernandez, G. (2011). Downregulation of the posterior medial frontal cortex prevents social conformity. J Neurosci 31, 11934-11940.
35. Klucharev, V., Smidts, A., and Fernandez, G. (2008). Brain mechanisms of persuasion: how 'expert power' modulates memory and attitudes. Soc Cogn Affect Neurosci 3, 353-366.
36. Knutson, B., Adams, C.M., Fong, G.W., and Hommer, D. (2001). Anticipation of increasing monetary reward selectively recruits nucleus accumbens. Journal of Neuroscience 21, 105.
37. Knutson, B., and Cooper, J.C. (2005). Functional magnetic resonance imaging of rewa1 rd prediction. Curr Opin Neurol 18, 411-417.
38. Lieberman, M.D. (2010). Social cognitive neuroscience, in Handbook of Social Psychology, eds. S. Fiske, D. Gilbert & G. Lindzey. 5th ed (New York, NY: McGraw-Hill), 143-193.
39. Mason, M.F., Dyer, R.G., and Norton, M.I. (2009). Neural mechanisms of social influence. Organizational Behavior and Human Decision Processes 110, 152-159.
40. Mcclure, S.M., York, M.K., and Montague, P.R. (2004). The neural substrates of reward processing in humans: the modern role of FMRI. Neuroscientist 10, 260-268.
41. Mehl, M.R., Pennebaker, J.W., Crow, D.M., Dabbs, J., and Price, J.H. (2001). The Electronically Activated Recorder (EAR): a device for sampling naturalistic daily activities and conversations. Behav Res Methods Instrum Comput 33, 517-523.
42. Meyer, M.L., Spunt, R.P., Berkman, E.T., Taylor, S.E., and Lieberman, M.D. (in press). Evidence for social working memory from a parametric functional MRI (fMRI) study. Proceedings of the National Academy of Science
43. Nisbet, M.C., and Kotcher, J.E. (2009). A Two-Step Flow of Influence? Opinion-Leader Campaigns on Climate Change. Science Communication 30, 328-354.
44. Nisbett, R., and Wilson, T. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review 84, 231-259.
45. O'connor, B., Balasubramanyan, R., Routledge, B., and Smith, N. (Year). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series, in: Proceedings of the International AAAI Conference on Weblogs and Social Media).
46. Pang, B., and Lee, L. (2004). A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts, in: Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics. (Barcelona, Spain: Association on for Computational Linguistics).
47. Pang, B., and Lee, L. (2008). Opinion Mining and Sentiment Analysis. Found. Trends Inf. 2, 1-135.
48. Pang, B., Lee, L., and Vaithyanathan, S. (2002). Thumbs up?: sentiment classification using machine learning techniques, in: Proceedings of the ACL-02 conference on Empirical methods in natural language processing-Volume 10. Association for Computational Linguistics).
49. Pennebaker, J.W. (2011). The Secret Life of Pronouns: What our words say about us. New Bloomsbury Press.
50. Perkins, J. (2011). text-processing. com [Online]. Available: http://text-processing.com/ [Accessed 12/17/2011 2011].
51. Petty, R.E., and Cacioppo, J.T. (1986a). Communication and persuasion: Central and peripheral routes to attitude change. NewYork: Springer-Verlag.
52. Petty, R.E., and Cacioppo, J.T. (1986b). The elaboration likelihood model of persuasion. Advances in experimental social psychology 19, 123-205.
53. Plassmann, H., O'doherty, J., Shiv, B., and Rangel, A. (2008). Marketing actions can modulate neural representations of experienced pleasantness. Proc Natl Acad Sci U S A 105, 1054.
54. Poldrack, R.A. (2008). The role of fMRI in cognitive neuroscience: where do we stand? Curr Opin Neurobiol 18, 223-227.
55. R Development Core Team (2011). R: A Language and Environment for Statistical Computing. (Vienna, Austria).
56. Rogers, E.M. (1995). Diffusion of Innovations. New York, NY: Free Press1.
57. Saxe, R. (2010). The right temporo-parietal junction: a specific brain region for thinking about thoughts, in Handbook of Theory of Mind, eds. A. Leslie & T. German.).
58. Schooler, J.W., Smallwood, J., Christoff, K., Handy, T.C., Reichle, E.D., and Sayette, M.A. (2011). Meta-awareness, perceptual decoupling and the wandering mind. Trends Cogn Sci 15, 319-326.
59. Sinclair, J.M. (2004). Trust The Text: Language, Corpus and Discourse. London: Routledge.
60. Smith, T., Coyle, J.R., Lightfoot, E., and Scott, A. (2007). Reconsidering models of influence: The relationship between consumer social networks and word-of-mouth effectiveness. Journal of Advertising Research 47, 387-396.
61. Spunt, R.P., and Lieberman, M.D. (2012). Dissociating modality-specific and supramodal neural systems for action understanding. J Neurosci 32, 3575-3583.
62. Stephens, G.J., Silbert, L.J., and Hasson, U. (2010). Speaker-listener neural coupling underlies successful communication. Proc Natl Acad Sci U S A 107, 14425-14430.
63. Subramani, M., and Rajagopalan, B. (2003). Knowledge-Sharing and Influence in Online Social Networks via Viral Marketing Communications of the ACM 46, 300-307.
64. Tumasjan, A., Sprenger, T.O., Sandner, P.G., and Welpe, I.M. (Year). Predicting elections twitter: What 140 characters reveal about political sentiment, in: Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media), 178-185.
65. Ward, B.D. (2000). Simulateneous Inference for FMRI Data (AlphaSim). AlphaSim: AFNI version=AFNI_2011_12_21_1014 (Jan 28 2012) ed.: Biophysics Research Institute, Medical College of Wisconsin). 24
66. Webb, T., and Sheeran, P. (2006). Does changing behavioral intentions engender behavi1 or change? A meta-analysis of the experimental evidence. Psychological Bulletin 132, 249-268.
67. Wilson, T., and Schooler, J. (1991). Thinking Too Much: Introspection can reduce the quality of preferences and decisions. Journal of Personality and Social Psychology 60, 181-192.
68. Wojnicki, A.C., and Godes, D. (2008). Word-of-Mouth as Self-Enhancement HBS Marketing Research Paper No. 06-01.
69. Zaki, J., Schirmer, J., and Mitchell, J.P. (2011). Social influence modulates the neural computation of value. Psychol Sci 22, 894-900.
70. Zaki, J., Weber, J., Bolger, N., and Ochsner, K. (2009). The neural bases of empathic accuracy. Proc Natl Acad Sci 106, 11382-11387.