Hostname: page-component-745bb68f8f-f46jp Total loading time: 0 Render date: 2025-01-13T18:18:40.631Z Has data issue: false hasContentIssue false
  • English
  • Français

Mapping collective behavior in the big-data era

Published online by Cambridge University Press:  26 February 2014

R. Alexander Bentley ,
Michael J. O'Brien  and
William A. Brock
R. Alexander Bentley
Affiliation:
Department of Archaeology and Anthropology, University of Bristol, Bristol BS8 1UU, United Kingdom. r.a.bentley@bristol.ac.ukhttp://www.alex-bentley.com
Michael J. O'Brien
Affiliation:
Department of Anthropology, University of Missouri, Columbia, MO 65211obrienm@missouri.eduhttp://cladistics.coas.missouri.edu
William A. Brock
Affiliation:
Department of Economics, University of Missouri, Columbia, MO 65211; and Department of Economics, University of Wisconsin, Madison, WI 53706wbrock@scc.wisc.eduhttp://www.ssc.wisc.edu/~wbrock/
Get access Rights & Permissions [Opens in a new window]

Abstract

The behavioral sciences have flourished by studying how traditional and/or rational behavior has been governed throughout most of human history by relatively well-informed individual and social learning. In the online age, however, social phenomena can occur with unprecedented scale and unpredictability, and individuals have access to social connections never before possible. Similarly, behavioral scientists now have access to “big data” sets – those from Twitter and Facebook, for example – that did not exist a few years ago. Studies of human dynamics based on these data sets are novel and exciting but, if not placed in context, can foster the misconception that mass-scale online behavior is all we need to understand, for example, how humans make decisions. To overcome that misconception, we draw on the field of discrete-choice theory to create a multiscale comparative “map” that, like a principal-components representation, captures the essence of decision making along two axes: (1) an east–west dimension that represents the degree to which an agent makes a decision independently versus one that is socially influenced, and (2) a north–south dimension that represents the degree to which there is transparency in the payoffs and risks associated with the decisions agents make. We divide the map into quadrants, each of which features a signature behavioral pattern. When taken together, the map and its signatures provide an easily understood empirical framework for evaluating how modern collective behavior may be changing in the digital age, including whether behavior is becoming more individualistic, as people seek out exactly what they want, or more social, as people become more inextricably linked, even “herdlike,” in their decision making. We believe the map will lead to many new testable hypotheses concerning human behavior as well as to similar applications throughout the social sciences.

Keywords

agentscopyingdecision makingdiscrete-choice theoryinnovationnetworkstechnological change
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 37 , Issue 1 , February 2014 , pp. 63 - 76
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adamic, L. A. & Huberman, B. A. (2000) Power-law distribution of the World Wide Web. Science 287:2115.CrossRefGoogle Scholar
Aldrich, D. P. (2012) How to weather a hurricane. New York Times, August 2, 2012, p. A27.Google Scholar
Allen, D. & Wilson, T. D. (2003) Information overload: Context and causes. New Review of Information Behaviour Research 4:31–44.CrossRefGoogle Scholar
Allen, P. M. & McGlade, J. M. (1986) Dynamics of discovery and exploitation: The case of the Scotian Shelf groundfish fisheries. Canadian Journal of Fisheries and Aquatic Science 43:1187–200.CrossRefGoogle Scholar
Alvergne, A., Gurmu, E., Gibson, M. A. & Mace, R. (2011) Social transmission and the spread of modern contraception in rural Ethiopia. PLoS ONE 6(7):e22515.Google Scholar
Alves, R. R. N. & Rosa, I. M. L. (2007) Biodiversity, traditional medicine and public health: Where do they meet? Journal of Ethnobiology and Ethnomedicine 3:14.CrossRefGoogle Scholar
Amaral, L. A. N., Scala, A., Barthélémy, M. & Stanley, H. E. (2000) Classes of small-world networks. Proceedings of the National Academy of Sciences USA 97:11149–52.Google Scholar
Amaro de Matos, J. & Perez, J. (1991) Fluctuations in the Curie–Weiss version of the random field Ising model. Journal of Statistical Physics 6:587–608.CrossRefGoogle Scholar
Apicella, C. L., Marlowe, F. W., Fowler, J. H. & Christakis, N. A. (2012) Social networks and cooperation in hunter–gatherers. Nature 481:497–501.CrossRefGoogle ScholarPubMed
Aral, S. & Walker, D. (2012) Identifying influential and susceptible members of social networks. Science 337:337–41.CrossRefGoogle ScholarPubMed
Arawatari, R. (2009) Informatization, voter turnout and income inequality. Journal of Economic Inequality 7:29–54.CrossRefGoogle Scholar
Atkisson, C., O'Brien, M. J. & Mesoudi, A. (2012) Adult learners in a novel environment use prestige-biased social learning. Evolutionary Psychology 10:519–37.Google Scholar
Barabási, A.-L. & Albert, R. (1999) Emergence of scaling in random networks. Science 286(5439):509–12. Available at: http://www.ncbi.nlm.nih.gov/pubmed/10521342.Google Scholar
Baron, J. (2007) Thinking and deciding, 3rd and 4th editions. Cambridge University Press.Google Scholar
Basalla, G. (1989) The evolution of technology. Cambridge University Press.Google Scholar
Bates, B. R., Romina, S., Ahmed, R. & Hopson, D. (2006) The effect of source credibility on consumers' perceptions of the quality of health information on the Internet. Medical Informatics and the Internet in Medicine 31:45–52.CrossRefGoogle ScholarPubMed
Batty, M. (2006) Rank clocks. Nature 444:592–96.Google Scholar
Baumeister, R. F. & Tierney, J. (2011) Willpower: Rediscovering the greatest human strength. Penguin.Google Scholar
Becker, G. S. (1962) Irrational behavior and economic theory. Journal of Political Economy 70:1–13.CrossRefGoogle Scholar
Becker, G. S. (1976) The economic approach to human behavior. University of Chicago Press.CrossRefGoogle Scholar
Becker, G. S. (1991) A treatise on the family, enlarged edition. Harvard University Press.CrossRefGoogle Scholar
Beinhocker, E. D. (2006) The origin of wealth: evolution, complexity, and the radical remaking of economics. Random House.Google Scholar
Belefant-Miller, H. & King, D. W. (2001) How, what, and why science faculty read. Science and Technology Libraries 19:91–112.CrossRefGoogle Scholar
Benotsch, E. G., Kalichman, S. & Weinhardt, L. S. (2004) HIV–AIDS patients' evaluations of health information on the Internet: The digital divide and vulnerability to fraudulent claims. Journal of Consulting and Clinical Psychology 72:1004–11.Google Scholar
Bentley, R. A., Earls, M. & O'Brien, M. J. (2011) I'll have what she's having: Mapping social behavior. MIT Press.Google Scholar
Bentley, R. A., Garnett, P., O'Brien, M. J. & Brock, W. A. (2012) Word diffusion and climate science. PLoS ONE 7(11):e47966.CrossRefGoogle ScholarPubMed
Bentley, R. A., Lipo, C. P., Hahn, M. W. & Herzog, H. A. (2007) Regular rates of popular culture change reflect random copying. Evolution and Human Behavior 28:151–58.Google Scholar
Bentley, R. A. & Maschner, H. D. G. (2000) A growing network of ideas. Fractals 8:227–37.CrossRefGoogle Scholar
Bentley, R. A. & O'Brien, M. J. (2011) The selectivity of social learning and the tempo of cultural evolution. Journal of Evolutionary Psychology 9:125–41.CrossRefGoogle Scholar
Bentley, R. A. & O'Brien, M. J. (2012) The buzzwords of the crowd. New York Times, December 1, 2012, p. SR4.Google Scholar
Bentley, R. A. & Ormerod, P. (2010) A rapid method for assessing social versus independent interest in health issues: A case study of “bird flu” and “swine flu”. Social Science and Medicine 71(3):482–85.CrossRefGoogle ScholarPubMed
Berger, J. & Le Mens, G. (2009) How adoption speed affects the abandonment of cultural tastes. Proceedings of the National Academy of Sciences USA 106:8146–50.CrossRefGoogle ScholarPubMed
Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C. & West, G. B. (2007a) Growth, innovation, scaling, and the pace of life in cities. Proceedings of the National Academy of Sciences USA 104:7301–6.CrossRefGoogle ScholarPubMed
Bettencourt, L. M. A., Lobo, J. & Strumsky, D. (2007b) Invention in the city: Increasing returns to patenting as a scaling function of metropolitan size. Research Policy 36:107–20.CrossRefGoogle Scholar
Bettinger, R. L., Boyd, R. & Richerson, P. J. (1996) Style, function and cultural evolutionary processes. In: Darwinian archeologies, ed. Maschner, H. D. G., pp. 133–62. Plenum Press.Google Scholar
Biermann, J. S., Golladay, G. J., Greenfield, M. L. V. H. & Baker, L. H. (1999) Evaluation of cancer information on the Internet. Cancer 86:381–90.Google Scholar
Bordieu, P. (1990) The logic of practice. Stanford University Press.CrossRefGoogle Scholar
Borgatti, S. P., Mehra, A., Brass, D. J. & Labianca, G. (2009) Network analysis in the social sciences. Science 323:892–95.CrossRefGoogle ScholarPubMed
Brock, W. A. & Durlauf, S. N. (1999) A formal model of theory choice in science. Economic Theory 14:113–30.Google Scholar
Brock, W. A. & Durlauf, S. N. (2001b) Interactions-based models. In: Handbook of econometrics, vol. 5, ed. Heckman, J. & Leamer, E., pp. 3297–80. Elsevier Science.Google Scholar
Burling, R. (1993) Primate calls, human language, and nonverbal communication. Current Anthropology 34:25–53.CrossRefGoogle Scholar
Byrne, R. W. & Russon, A. E. (1998) Learning by imitation: A hierarchical approach. Behavioral and Brain Sciences 21:667–721.CrossRefGoogle ScholarPubMed
Caldwell, C. A. & Whiten, A. (2002) Evolutionary perspectives on imitation: Is a comparative psychology of social learning possible? Animal Cognition 5:193–208.Google Scholar
Carr, N. (2008) Is Google making us stupid? The Atlantic, July/August 2008, pp. 56–63.Google Scholar
Cavalli-Sforza, L. L. & Feldman, M. W. (1981) Cultural transmission and evolution. Princeton University Press.Google ScholarPubMed
Centola, D. (2010) The spread of behavior in an online social network experiment. Science 329:1194–97.Google Scholar
Cha, M., Benevenuto, F., Haddadi, H. & Gummadi, K. P. (2012) The world of connections and information flow in Twitter. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans 42:991–98.Google Scholar
Cha, M., Haddadi, H., Benevenuto, F. & Gummadi, K. P. (2010) Measuring user influence in Twitter: The million follower fallacy. In: Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media, ed. Hearst, M. A., Cohen, W. & Gosling, S., pp. 10–17. AAAI Press.Google Scholar
Christakis, N. A. & Fowler, J. H. (2007) The spread of obesity in a large social network over 32 years. New England Journal of Medicine 357:370–79.Google Scholar
Clauset, A., Shalizi, C. R. & Newman, M. E. J. (2009) Power-law distributions in empirical data. SIAM Review 51:661–703.Google Scholar
Couzin, I. D., Ioannou, C. C., Demirel, G., Gross, T., Torney, C. J., Hartnett, A., Conradt, L., Levin, S. A. & Leonard, N. E. (2011) Uninformed individuals promote democratic consensus in animal groups. Science 334:1578–80.Google Scholar
Couzin, I. D., Krause, J., Franks, N. R. & Levin, S. A. (2005) Effective leadership and decision making in animal groups on the move. Nature 433:513–16.Google Scholar
Davis, A. & Fu, D. (2004) Culture matters: Decision making through increased awareness. Interservice/Industry Training, Simulation, and Education Conference Paper, No. 1852, pp. 1–9.Google Scholar
Dennett, D. (1995) Darwin's dangerous idea. Simon and Schuster.Google Scholar
de Sola Price, D. J. (1965) Networks of scientific papers. Science 149:510–15.Google Scholar
Dodds, P. S. & Watts, D. J. (2005) A generalized model of social and biological contagion. Journal of Theoretical Biology 232:587–604.CrossRefGoogle ScholarPubMed
Dreber, A., Rand, D. G., Fudenberg, D. & Nowak, M. A. (2008) Winners don't punish. Nature 452:348–51.CrossRefGoogle ScholarPubMed
Dunbar, R. I. M. (1992) Neocortex size as a constraint on group size in primates. Journal of Human Evolution 22:469–93.Google Scholar
Dunbar, R. I. M. (1993) Coevolution of neocortical size, group size and language in humans. Behavioral and Brain Sciences 16:681–735.Google Scholar
Dunbar, R. I. M. (1998) The social brain hypothesis. Evolutionary Anthropology 6:178–90.3.0.CO;2-8>CrossRefGoogle Scholar
Durlauf, S. (1999) How can statistical mechanics contribute to social science? Proceedings of the National Academy of Sciences USA 96:10582–84.CrossRefGoogle ScholarPubMed
Durlauf, S. (2002) On the empirics of social capital. Economic Journal 112:F459–79.Google Scholar
Dyson-Hudson, N. (1966) Karimojong politics. Clarendon Press.Google Scholar
Ehrenberg, A. S. C. (1959) The pattern of consumer purchases. Journal of the Royal Statistical Society C 8:26–41.Google Scholar
Eriksson, K., Enquist, M. & Ghirlanda, S. (2007) Critical points in current theory of conformist social learning. Journal of Evolutionary Psychology 5:67–87.Google Scholar
Eriksson, K., Jansson, F. & Sjöstrand, J. (2010) Bentley's conjecture on popularity toplist turnover under random copying. Ramanujan Journal 23:371–96.CrossRefGoogle Scholar
Evans, J. A. & Foster, J. G. (2011) Metaknowledge. Science 331:721–25.Google Scholar
Evans, T. & Giometto, A. (2011) Turnover rate of popularity charts in neutral models. arXiv:1105.4044v1. (Online publication)Google Scholar
Farmer, J. D., Patelli, P. & Zovko, I. I. (2005) The predictive power of zero intelligence in financial markets. Proceedings of the National Academy of Sciences USA 102:2254–59.Google Scholar
Frank, S. A. (2009) The common patterns of nature. Journal of Evolutionary Biology 22:1563–85.Google Scholar
Fratkin, E. M. (1989) Household variation and gender inequality in Ariaal Rendille pastoral production. American Anthropologist 91:45–55.Google Scholar
Gantz, J. & Reinsel, D. (2011) Extracting value from chaos. Available at: www.emc.com/digital_universe.Google Scholar
George, H. R., Swami, V., Cornelissen, P. L. & Tovee, M. J. (2008) Preferences for body mass index and waist-to-hip ratio do not vary with observer age. Journal of Evolutionary Psychology 6:207–18.CrossRefGoogle Scholar
Gillespie, J. H. (2004) Population genetics: A concise guide, 2nd edition. Johns Hopkins University Press.Google Scholar
Gintis, H. (2007) A framework for the unification of the behavioral sciences. Behavioral and Brain Sciences 30(1):1–61.CrossRefGoogle ScholarPubMed
Gintis, H. (2009) The bounds of reason: Game theory and the unification of the behavioral sciences. Princeton University Press.Google Scholar
Giving USA Foundation (2007) Giving USA 2007: Annual Report on Philanthropy for the year 2006. Giving USA Foundation.Google Scholar
Golder, S. A. & Macy, M. W. (2011) Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures. Science 333:1878–81.Google Scholar
Goodhardt, G. J., Ehrenberg, A. S. C. & Chatfield, C. (1984) The Dirichlet: A comprehensive model of buying behaviour. Journal of the Royal Statistical Society A 147:621–55.CrossRefGoogle Scholar
Hamilton, M. J., Milne, B. T., Walker, R. S., Burger, O. & Brown, J. H. (2007) The complex structure of hunter–gatherer social networks. Proceedings of the Royal Society of London B 274:2195–202.Google Scholar
Hausmann, R., Hidalgo, C. A., Bustos, S., Coscia, M., Chung, S., Jimemez, J., Simoes, A. & Yildirim, M. A. (2011) The atlas of economic complexity: Mapping paths to prosperity. Center for International Development, Harvard University.Google Scholar
Helbing, D. & Yu, W. (2009) The outbreak of cooperation among success-driven individuals under noisy conditions. Proceedings of the National Academy of Sciences USA 106:3680–85.Google Scholar
Helbing, D., Farkas, I. & Vicsek, T. (2000) Simulating dynamical features of escape panic. Nature 407:487–90.Google Scholar
Hemp, P. (2009) Death by information overload. Harvard Business Review 87(9):82–89.Google Scholar
Henrich, J. (2004) Demography and cultural evolution: Why adaptive cultural processes produced maladaptive losses in Tasmania. American Antiquity 69:197–214.Google Scholar
Henrich, J. (2010) The evolution of innovation-enhancing institutions. In: Innovation in cultural systems: Contributions from evolutionary anthropology, ed. O'Brien, M. J. & Shennan, S. J., pp. 99–120. MIT Press.Google Scholar
Henrich, J., and Gil-White, F. J. (2001) The evolution of prestige: Freely conferred deference as a mechanism for enhancing the benefits of cultural transmission. Evolution and Human Behavior 22:165–96.CrossRefGoogle ScholarPubMed
Henrich, J., Boyd, R., Bowles, S., Camerer, C., Gintis, H., McElreath, R. & Fehr, E. (2001) In search of Homo economicus: Experiments in 15 small-scale societies. American Economic Review 91:73–79.Google Scholar
Henrich, J., Boyd, R., Bowles, S., Gintis, H., Fehr, E., Camerer, C., McElreath, R., Gurven, M., Hill, K., Barr, A., Ensminger, J., Tracer, D., Marlow, F., Patton, J., Alvard, M., Gil-White F. & Henrich, N. (2005) “Economic Man” in cross-cultural perspective: Ethnography and experiments from 15 small-scale societies. Behavioral and Brain Sciences 28:795–855.CrossRefGoogle ScholarPubMed
Henrich, J., Heine, S. J. & Norenzayan, A. (2010) The weirdest people in the world? Behavioral and Brain Sciences 33:61–135.Google Scholar
Henrich, J., McElreath, R., Bar, A., Ensminger, J., Barrett, C., Bolyanatz, A., Cardenas, J. C., Gurven, M., Gwako, E., Henrich, N., Lesorogol, C., Marlowe, F., Tracer, D. & Ziker, J. (2006) Costly punishment across human societies. Science 312:1767–70.Google Scholar
Heyes, C. M. (1994) Social learning in animals: Categories and mechanisms. Biological Reviews 69:207–31.Google Scholar
Hill, K. R., Walker, R. S., Božicčević, M., Eder, J., Headland, T., Hewlett, B., Hurtad, A. M., Marlowe, F., Wiessner, P. & Wood, B. (2011) Co-residence patterns in hunter–gatherer show unique human social structure. Science 331:1286–89.Google Scholar
Hill, N. & Alexander, J. (2006) Handbook of customer satisfaction and loyalty measurement. Gower.Google Scholar
Hill, R. A., Bentley, R. A. & Dunbar, R. I. M. (2008) Network scaling reveals consistent fractal pattern in hierarchical mammalian societies. Biology Letters 4:748–51.Google Scholar
Horton, J. J., Rand, D. G. & Zeckhauser, R. J. (2011) The online laboratory: Conducting experiments in a real labor market. Experimental Economics 14:399–425.Google Scholar
Huberman, B. A. & Adamic, L. A. (1999) Growth dynamics of the World-Wide Web. Nature 401:131.Google Scholar
Hyde, J. S. & Linn, M. C. (2009) Gender similarities in mathematics and science. Science 314:599–600.Google Scholar
Ingram, H. M. & Stern, P. C. (2007) Research and networks for decision support in the NOAA Sectoral Applications Research Program. National Academies Press.Google Scholar
Jones, D. (2010) Human kinship, from conceptual structure to grammar. Behavioral and Brain Sciences 33:367–416.Google Scholar
Kahneman, D. (2003) Maps of bounded rationality: Psychology for behavioral economics. American Economic Review 93:1449–75.Google Scholar
Kandler, A., Laland, K.N. (2009) An investigation of the relationship between innovation and cultural diversity. Theoretical Population Biology 76:59–67.Google Scholar
Kessler, D. A., Maruvka, Y. E., Ouren, J. & Shnerb, N. M. (2012) You name it – How memory and delay govern first name dynamics. PLoS ONE 7(6):e38790.Google Scholar
Kikumbih, N., Hanson, K., Mills, A., Mponda, H. & Schellenberg, J. A. (2005) The economics of social marketing: The case of mosquito nets in Tanzania. Social Science and Medicine 60:369–81.Google Scholar
Kitcher, P. (1993) The advancement of science. Oxford University Press.Google Scholar
Kline, M. A. & Boyd, R. (2010) Population size predicts technological complexity in Oceania. Proceedings of the Royal Society B 277:2559–64.Google Scholar
Koerper, H. C. & Stickel, E. G. (1980) Cultural drift: A primary process of culture change. Journal of Anthropological Research 36:463–69.Google Scholar
Krakauer, D. (2011) Darwinian demons, evolutionary complexity, and information maximization. Chaos 21:037110.Google Scholar
Krugman, P. (2012) The power (law) of Twitter. New York Times blogpost February 8, 2012. Available at: http://nyti.ms/zVLT72 Google Scholar
Laherrère, J. & Sornette, D. (1998) Stretched exponential distributions in nature and economy: “Fat tails” with characteristic scales. European Physical Journal B 2:525–39.Google Scholar
Laland, K. N. & Brown, G. R. (2011) Sense and nonsense: Evolutionary perspectives on human behaviour, 2nd edition. Oxford University Press.Google Scholar
Laland, K. N. (2004) Social learning strategies. Learning and Behavior 32:4–14.Google Scholar
Laland, K. N., Odling-Smee, F. J. & Myles, S. (2010) How culture shaped the human genome: Bringing genetics and the human sciences together. Nature Reviews Genetics 11:137–48.CrossRefGoogle ScholarPubMed
Lenton, A. P., Fasolo, B. & Todd, P. M. (2008) “Shopping” for a mate: Expected vs. experienced preferences in online mate choice. IEEE Transactions on Professional Communication (Special Section: Darwinian Perspectives on Electronic Communication) 51:169–82.Google Scholar
Lenton, A. P., Fasolo, B. & Todd, P. M. (2009) The relationship between number of potential mates and mating skew in humans. Animal Behaviour 77:55–60.Google Scholar
Lewis, I. (1961) A pastoral democracy. Oxford University Press.Google Scholar
Lewis, K., Gonzalez, M. & Kaufman, J. (2011) Social selection and peer influence in an online social network. Proceedings of the National Academy of Sciences USA 109:68–72.Google Scholar
Lewis, K., Kaufman, J., Gonzalez, M., Wimmer, A. & Christakis, N. (2008) Taste, times, and ties: A new social network dataset using Facebook.com. Social Networks 30:330–42.Google Scholar
Li, J. & Lee, L. (2009) Binary choice under social interactions: An empirical study with and without subjective data on expectations. Journal of Applied Econometrics 24:257–81.Google Scholar
Lieberman, E., Hauert, C. & Nowak, M. A. (2005) Evolutionary dynamics on graphs. Nature 433:312–16.CrossRefGoogle Scholar
Lieberman, E., Michel, J.-B., Jackson, J., Tang, T. & Nowak, M. A. (2007) Quantifying the evolutionary dynamics of language. Nature 449:713–16.Google Scholar
Lorenz, J., Rauhut, H., Schweitzer, F. & Helbing, D. (2011) How social influence can undermine the wisdom of crowd effect. Proceedings of the National Academy of Sciences USA 108:9020–25.Google Scholar
Low, B. S. (2001) Why sex matters: A Darwinian look at human behavior. Princeton University Press.Google Scholar
Mace, R. & Colleran, H. (2009) Kin influence on the decision to start using modern contraception: A longitudinal study from rural Gambia. American Journal of Human Biology 21:472–77.Google Scholar
Malmgren, R. D., Ottino, J. M. & Nunes Amaro, L. A. (2010) The role of mentorship in protégé performance. Nature 465:622–26.Google Scholar
Manski, C. F. (1993) Identification of endogenous social effects: The reflection problem. Review of Economic Studies 60:531–42.CrossRefGoogle Scholar
Marshall, E. (2000) Reinventing an ancient cure for malaria. Science 290:437–39.Google Scholar
Masucci, A. P., Kalampokis, A., Martínez Equíluz, V. & Hernández-García, E. (2011) Wikipedia information flow analysis reveals the scale-free architecture of the semantic space. PLoS ONE 6(2):e17333.Google Scholar
Mateos, P., Longley, P. A. & O'Sullivan, D. (2011) Ethnicity and population structure in personal naming networks. PLoS ONE 6(9):e22943.Google Scholar
McCarty, N. M., Poole, K. T. & Rosenthal, H. (2006) Polarized America: The dance of ideology and unequal riches. MIT Press.Google Scholar
McFadden, D. L. (2001) Economic choices. American Economic Review 91:351–78.Google Scholar
Mesoudi, A. (2008) An experimental simulation of the “copy-successful-individuals” cultural learning strategy: Adaptive landscapes, producer–scrounger dynamics, and informational access costs. Evolution and Human Behavior 29:350–63.Google Scholar
Mesoudi, A. (2011) Cultural evolution: How Darwinian theory can explain human culture and synthesize the social sciences. University of Chicago Press.Google Scholar
Mesoudi, A. & Lycett, S. J. (2009) Random copying, frequency-dependent copying and culture change. Evolution and Human Behavior 30:41–48.Google Scholar
Mesoudi, A., Whiten, A. & Laland, K. N. (2006) Towards a unified science of cultural evolution. Behavioral and Brain Sciences 29:329–83.Google Scholar
Milot, E., Mayer, F. M., Nussey, D. H., Boisvert, M., Pelletier, F. & Réale, D. (2011) Evidence for evolution in response to natural selection in a contemporary human population. Proceedings of the National Academy of Sciences USA 108:17040–45.Google Scholar
Nagle, T. T. & Holden, R. K. (2002) The strategy and tactics of pricing. Prentice-Hall.Google Scholar
Nettle, D. (2009) Ecological influences on human behavioural diversity: A review of recent findings. Trends in Ecology and Evolution 24:618–24.Google Scholar
Nettle, D. (2010) Understanding of evolution may be improved by thinking about people. Evolutionary Psychology 8:205–28.CrossRefGoogle ScholarPubMed
Nestle, M. & Nesheim, M. (2012) Why calories count: From science to politics. University of California Press.Google Scholar
Newman, M. E. J. (2005) Power laws, Pareto distributions and Zipf's law. Contemporary Physics 46:323–51.Google Scholar
O'Brien, M. J. & Bentley, R. A. (2011) Stimulated variation and cascades: Two processes in the evolution of complex technological systems. Journal of Archaeological Method and Theory 18:309–35.Google Scholar
Ohtsuki, H., Hauert, C., Lieberman, E. & Nowak, M. A. (2006) A simple rule for the evolution of cooperation on graphs and social networks. Nature 441:502–505.Google Scholar
Onnela, J.-P. & Reed-Tsochas, F. (2010) Spontaneous emergence of social influence in online systems. Proceedings of the National Academy of Sciences USA 107:18375–80.Google Scholar
Ormerod, P. (2012) Positive linking: How networks can revolutionise the world. Faber and Faber.Google Scholar
Ouattara, K., Lemasson, A. & Zuberbühler, K (2009) Campbell's monkeys use affixation to alter call meaning. PLoS ONE 4(11):e7808.Google Scholar
Plous, S. (1993) The psychology of judgment and decision making. McGraw-Hill.Google Scholar
Postmes, T., Spears, R. & Cihangir, S. (2001) Quality of decision making and group norms. Journal of Personality and Social Psychology 80:918–30.Google Scholar
Powell, A., Shennan, S. & Thomas, M. G. (2009) Late Pleistocene demography and the appearance of modern human behavior. Science 324:1298–301.Google Scholar
Rand, D. G. (2012) The promise of Mechanical Turk: How online labor markets can help theorists run behavioral experiments. Journal of Theoretical Biology 299:172–79.Google Scholar
Rand, D. G., Dreber, A., Ellingsen, T., Fudenberg, D. & Nowak, M. A. (2009) Positive interactions promote public cooperation. Science 325:1272–75.Google Scholar
Reali, F. & Griffiths, T. L. (2010) Words as alleles: Connecting language evolution with Bayesian learners to models of genetic drift. Proceedings of the Royal Society B 277:429–36.CrossRefGoogle ScholarPubMed
Rendell, L., Fogarty, L., Hoppitt, W. J. E., Morgan, T. J. H., Webster, M. M. & Laland, K. N. (2011) Cognitive culture: Theoretical and empirical insights into social learning strategies. Trends in Cognitive Sciences 15:68–76.Google Scholar
Repetto, R. (2006) Punctuated equilibrium and the dynamics of U.S. environmental policy. Yale University Press.Google Scholar
Rogers, E. M. (1962) Diffusion of innovations. Free Press.Google Scholar
Romer, P. (2012) Process, responsibility, and Myron's Law. In: In the wake of the crisis: Leading economists reassess economic policy, ed. Blanchard, O. J., Romer, D., Spence, A. M. & Stigltiz, J. E., pp. 111–24. MIT Press.Google Scholar
Saavedra, S., Reed-Tsochas, F. & Uzzi, B. (2009) A simple model of bipartite cooperation for ecological and organizational networks. Nature 457:463–66.Google Scholar
Salganik, M. J., Dodds, P. S. & Watts, D. J. (2006) Experimental study of inequality and unpredictability in an artificial cultural market. Science 311(5762):854–56. doi:10.1126/science.1121066.Google Scholar
Salzman, P. C. (1999) Is inequality universal? Current Anthropology 40:31–61.Google Scholar
Sela, A. & Berger, J. (2012) Decision quicksand: How trivial choices suck us in. Journal of Consumer Research 39:360–70.Google Scholar
Shalizi, C. R. & Thomas, A. C. (2010) Homophily and contagion are genetically confounded in observational social network studies. Sociological Methods and Research 40:211–39.Google Scholar
Shennan, S. J. (2000) Population, culture history and the dynamics of culture change. Current Anthropology 41:811–35.CrossRefGoogle Scholar
Simkin, M. V. & Roychowdhury, V. P. (2003) Read before you cite! Complex Systems 14:269.Google Scholar
Simon, H. A. (1955) A behavioral model of rational choice. Quarterly Journal of Economics 69:99–118.Google Scholar
Sparrow, B., Liu, J. & Wegner, D. M. (2011) Google effects on memory: Cognitive consequences of having information at our fingertips. Science 333:776–78.Google Scholar
Strauss, S. (2012) Six reasons why political polarization will only get worse. Huffington Post (October 14). Available at: http://www.huffingtonpost.com/steven-strauss/megatrend-six-reasons-ame_b_1965182.html.Google Scholar
Stringer, M. J., Sales-Pardo, M. & Amaral, L. A. N. (2010) Statistical validation of a global model for the distribution of the ultimate number of citations accrued by papers published in a scientific journal. Journal of the American Society for Information Science and Technology 61:1377–85.Google Scholar
Sumecki, D., Chipulu, M. & Ojiako, U. (2011) Email overload: Exploring the moderating role of the perception of email as a “business critical” tool. International Journal of Information Management 31:407–14.Google Scholar
Surowiecki, J. (2004) The wisdom of crowds: Why the many are smarter than the few. Abacus.Google Scholar
Toffler, A. (1970) Future shock. Random House.Google Scholar
Tomasello, M., Carpenter, M., Call, J., Behne, T. & Moll, H. (2005) Understanding and sharing intentions: The origins of cultural cognition. Behavioral and Brain Sciences 28:675–735.Google Scholar
Tomasello, M., Kruger, A. C. & Ratner, H. H. (1993) Cultural learning. Behavioral and Brain Sciences 16:495–511.Google Scholar
Tsetsos, K., Chater, K. & Usher, M. (2012) Salience driven value integration explains decision biases and preference reversal. Proceedings of the National Academy of Sciences USA 109:9659–64.Google Scholar
Twenge, J., Campbell, K. W. & Gentile, B. (2012) Increases in individualistic words and phrases in American books, 1960–2008. PLoS ONE 7(7):e40181.Google Scholar
United Nations (2006) World urbanization prospects: The 2005 revision. United Nations.Google Scholar
Venditti, C., Meade, A. & Pagel, M. (2010) Phylogenies reveal new interpretation of speciation and the Red Queen. Nature 463:349–52.Google Scholar
Viswanath, B., Mislove, A., Cha, M. & Gummadi, K. P. (2009) On the evolution of user interaction in Facebook. In: Proceedings of the 2nd ACM Workshop on Online Social Networks, ed. Crowcroft, J. & Krishnamurthy, B., pp. 37–42. Association for Computing Machinery.Google Scholar
Voeks, R. A. (1996) Tropical forest healers and habitat preference. Economic Botany 50:381–400.Google Scholar
Watts, D. J. & Hasker, S. (2006) Marketing in an unpredictable world. Harvard Business Review 84(9):25–30.Google Scholar
Wegner, D. M. (1995) A computer network model of human transactive memory. Social Cognition 13:319–39.Google Scholar
Winterhalder, B., Kennett, D. J., Grote, M. N. & Bartruff, J. (2010) Ideal free settlement of California's Northern Channel Islands. Journal of Anthropological Archaeology 29:469–90.Google Scholar
Winterhalder, B. & Smith, E. A. (2000) Analyzing adaptive strategies: Human behavioral ecology at twenty-five. Evolutionary Anthropology 9:51–72.Google Scholar
Wu, F. & Huberman, B. A. (2007) Novelty and collective attention. Proceedings of the National Academy of Sciences USA 104:17599–601.Google Scholar
Yule, G. U. (1924) A mathematical theory of evolution based on the conclusions of Dr. J. C. Willis. Philosophical Transactions of the Royal Society B 213:21–87.Google Scholar
Zipf, G. K. (1949) Human behavior and the principle of least effort. Addison-Wesley.Google Scholar
Zun, L. S., Blume, D. N., Lester, J., Simpson, G. & Downey, L. (2004) Accuracy of emergency medical information on the web. American Journal of Emergency Medicine 22:94–97.Google Scholar