Manifesto of computacional social science
DOI:
https://doi.org/10.5433/2176-6665.2013v18n1p20Keywords:
Manifesto, Computacional social science, Quantitative research, DatabasesAbstract
The increasing integration of technology into our lives has created unprecedented volumes of data on society's everyday behaviour. Such data opens up exciting new opportunities to work towards a quantitative understanding of our complex social systems, within the realms of a new discipline known as Computacional Social Science. Against a background of financial crises, riots and internacional epidemics, the urgent need for a greater comprehension of the complexity of our interconnected global society and an ability to apply such insights in policy decisions is clear. This manifesto outlines the objectives of this new scientific direction, considering the challenges involved in it, and the extensive impact on science, techonology, and society that the sucess of this endeavour is likely to bring about.Downloads
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References
AKERLOF, George A.; SHILLER, Robert J. Animal spirits: how human psychology drives the economy, and why it matters for global capitalism. Princeton: Princeton University Press, 2009.
ALÓS-FERRER, Carlos; KIRCHSTEIGER, Gerog. General equilibrium and the emergence of (non)market clearing trading institutions. Economic Theory, Berlin, v. 44, n. 3, p. 339-360, 2010.
ARTHUR, W. Brian. Out-of-equilibrium economics and agent-based modeling. In: TESFATSION,Leigh; JUDD, Kenneth L. Handbook of computacional economics: agent-based computacional economics. Oxford: Elsevier, 2005. v. 2, p. 1551-1563.
TESFATSION,Leigh; JUDD, Kenneth L. Inductive reasoning and bounded rationality. American Economic Review, Nashville, v. 84, p. 406, 1994.
AXELROD, Robert. The dissemination of culture: a model with local convergence and global polarization. Journal of Conflict Resolution, Newbury Park, v. 41, n. 2, p. 203- 226, 1997.
AXELROD, Robert. The evolution of cooperation. New York: Basic Books, 1984.
AXELROD, Robert. An evolutionary approach to norms. American Political Science Review, Baltimore, v. 80, n. 4, p. 1095-1111, 1986.
AXTELL, Robert L. et al. Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences, Washington, v. 99, p. 7275- 7279, 2002.
BAINBRIDGE, William Sims. The scientific research potential of virtual worlds. Science, Washington, v. 317, n. 5837, p. 472-476, 2007.
BALCAN, Duygu et al. Multiscale mobility networks and the spatial spreading of infectious diseases. Proceedings of the National Academy of Sciences, Washington, v. 106, n. 51, n. 21484-21489, 2009.
BENKLER, Yochai. Coase's penguin, or, linux and the nature of the firm. The Yale Law Journal, Yale, v. 112, n. 3, p. 369-446, 2002.
BICCHIERI, Cristina. The grammar of society: the nature and dynamics of social norms. Cambridge: Cambridge University Press, 2006.
BILLARI, Francesco C. et al. Agent-based computational modelling applications in demography, social, economic and environmental sciences. Heidelberg: Physica Verlag-Springer, 2006.
BORRILL, Paul L.; TESTFATSION, Leigh. Agent-based modeling: the right mathematics for the social sciences? In: DAVIS, Johan B.; HANDS, Wade. The elgar companion to recent economic methodology. New York: Edward Elgar Publishers, 2011. p. 228-258.
BRABHAM, Daren C. Crowdsourcing as a model for problem solving: an introduction and cases. Convergence, London, v. 14, n. 1, p. 75-90, 2008.
CASTELFRANCHI, Cristiano; CONTE, Rosaria. Microsimulation and the social science. Berlin: Springer-Verlag, 1996.
CASTELLO, Xavier et al. Viability and resilience of complex systems: concepts, methods and case studies from ecology and society. New York: Springer-Verlag, 2011.
CATTUTO, Ciro et al. Collective dynamics of social annotation. Proceedings of the National Academy of Sciences, Washington, v. 106, n. 26, p. 10511-10515, 2009.
CEDERMAN, Lars-Erik. Emergent actors in world politics: how states and nations develop. Princeton: Princeton University Press, 1997.
CENTOLA, Damon et al. Homophily, cultural drift, and the co-evolution of cultural groups. Journal of Conflict Resolution, Newbury Park, v. 51, n. 6, p. 905-929, 2007.
CHESNAIS, Jean-Claude. The demographic transition: stages, patterns, and economic implications: a longitudinal study of sixty-seven countries covering the period 1720– 1984. Oxford: Oxford University Press, 1993.
CHRISTAKIS, Nicolas A.; FOWLER, James H. The Spread of Obesity in a Large Social Network over 32 Years. The New England Journal of Medicine, New England, v. 357, p. 370-379, 2007.
CONTE, Rosaria et al. Sociology and social theory in agent based social simulation: a symposium. Computational and Mathematical Organization Theory, Pittsburgh, v. 7, n. 3, p. 183-205, 2001.
CONTE, Rosaria; ANDRIGHETTO, Giulia; CAMPENN, Marco (Ed.). Minding norms. Oxford: Oxford University Press, 2013.
CONTE, Rosaria; PAOLUCCI, Mario. Reputation in artificial societies: social beliefs for social control. Dordrecht: Kluwer, 2002.
DAREMA, Frederica. Grid computing and beyond: the context of dynamic data driven applications systems. Proceedings of the IEEE, New York, v. 93, p. 692-697, 2005.
DENNETT, Daniel C. Descartes error: emotion, reason and the human brain - Damasio, Ar. Times Literary Supplement, 25 ago. 1995. n. 3.
DUNBAR, Robin. The social brain hypothesis. Evolutionary Anthropology: issues, news, and reviews. New York, v. 6, n. 5, p. 178–190, 1998.
EBBERS, Joris J.; WIJNBERG, Nachoem M. Disentangling the effects of reputation and network position on the evolution of alliance networks. Strategic Organization, Thousand Oaks, v. 8, n. 3, p. 255-275, 2010.
EGULUZ, Victor M. et al. Cooperation and the emergence of role differentiation in the dynamics of social networks. American Journal of Sociology, Chicago, v. 110, n. 4, p. 977-1008, 2005.
EHRHARDT, George; MARSILI, Matteo; VEGA-REDONDO, Fernando. Phenomenological models of socioeconomic network dynamics. Physical Review, Melville, v. 74, n. 1, 2006.
EPSTEIN, Joshua M. Agent-based computational models and generative social science. Complexity, New York, v. 4, n. 5, p. 41–60, 1999.
EPSTEIN, Joshua M. Generative social science: studies in agent-based computational modeling. Princeton: Princeton University Press, 2007.
EPSTEIN, Joshua M. Learning to be thoughtless: social norms and individual computation. Computational Economics, Dordrecht, v. 18, p. 9-24, 2001.
EPSTEIN, Joshua M. Modeling civil violence: an agent-based computational approach. Proceedings of the National Academy of Sciences, Washington, v. 99, p. 7243-7250, 2002.
FALCONE, Rino; CASTELFRANCHI, Christiano. Trust theory: a socio-cognitive and computational. Model: Wiley, 2010.
FISHER, Ronald Aylmer. The genetical theory of natural selection. New York: Oxford Universit Press, 1930.
FLACHE, Andreas; MACY, Michael W. Local convergence and global diversity: from interpersonal to social influence. Journal of Conflict Resolution, Newbury Park, v. 55, n. 6, p. 970-995, 2011.
GALÁN, José Manuel et al. Errors and artefacts in agent-based modelling. Journal of Artificial Societies and Social Simulation, Surrey, v. 12, n. 1, 2009.
GAUVIN, Laetitia; VANNIMENUS, Jean; NADAL, Jean-Pierre. Phase diagram of a Schelling segregation model. The European Physical Journal B – Condensed Matter and Complex Systems, Les Ulis, v. 70, n. 2, p. 293-304, 2009.
GIARDINI, Francesca; CONTE, Rosaria. Gossip for social control in natural and artificial societies. Simulation, v. 88, n. 1, p. 18-32, 2012.
GILBERT, Nigel; CONTE, Rosaria (Ed.). Artificial societies: the computer simulation of social life. London: University College London Press, 1995.
GILBERT, Nigel; CONTE, Rosaria (Ed.). Artificial societies: the computer simulation of social life. London: University College London Press, 1995.
GINTIS, Herbert. The bounds of reason. Princeton: Princeton University Press, 2009.
GOLDER, Scott A.; HUBERMAN, Bernardo A. Usage patterns of collaborative tagging systems. Journal of Information Science, Cambridge, v. 32, p. 198-208, 2006.
GONZÁLEZ-AVELLA, Juan Carlos et al. Information feedback and mass media effects in cultural dynamics. Journal of Artificial Societies and Social Simulation, Surrey, v. 10, n. 3, 2007.
GRUJIC, Jelena et al. Social experiments in the mesoscale: humans playing a spatial prisoner's dilemma. PLoS ONE, San Francisco, v. 5, 2010.
HABIB, Laurence; LINE, Wittek. The portfolio as artifact and actor. Mind, Culture Activity, La Jolla, v. 14, n. 4, p. 266-282, 2007.
HAVLIN, Sales et al. Challenges in network science: applications to infrastructures, climate, social systems and economics. The European Physical Journal Special Topics, Les Ulis, v. 214, p. 273-293, 2012.
HELBING, Dirk et al. FuturICT: participatory computing to understand and manage our complex world in a more sustainable and resilient way. The European Physical Journal Special Topics, Heidelberg, v. 214, p. 11-39, 2012.
HELBING, Dirk. Pluralistic modeling of complex systems. Science and Culture, Calcutta, v. 76, p. 315-329, 2010.
HELBING, Dirk; BALIETTI, Stefano. From social data mining to forecasting socioeconomic crise. European Physical Journal: Special Topics, Heidelberg, v. 195, p. 3-68, 2011.
HELBING, Dirk; JOST, Jürgen; LANE, David. Social systems and complexity. Advances in Complex Systems, Amsterdam, v.11, n. 4, p. 485-486, 2008.
HELBING, Dirk; YU, Wenjian; RAUHUT, Heiko. Self-organization and emergence in social systems: modeling the coevolution of social environments and cooperative behavior. The Journal of Mathematical Sociology, London, v. 35, n. 1-3, p. 177-208, 2011.
HENRICH, Joseph et al. Markets, religion, community size, and the evolution of fairness and punishment. Science, Washington, v. 327, p. 1480-1484, 2010.
HUBER, George P. Organizational learning: the contributing processes and the literatures. Organization Science, Providence, v. 2, n. 1, p. 88-115, 1991.
KARSAI, Marton et al. Small but slow world: How network topology and burstiness slow down spreading. Physical Review, New York, v. 83, n. 2, p. 1-4, 2011.
KITTUR, Aniket. Crowdsourcing user studies with mechanical turk.In: ANNUAL SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 36., 2008, New York. Proceedings… New York: ACM, 2008.
KIUKKONEN, N. et al. Proceedings of international conference on pervasive services. Berlin: ACM, 2010.
LANE, Nicholas D. et al. A survey of mobile phone sensing. IEEE Communications Magazine, New York, v. 48, n. 9, p. 140-150, 2010.
LAZER, David et al. Computation social science. Science, Washington, v. 323, p. 721-724, 2009.
LEWIS, David. Convention: a philosophical study. Harvard: Harvard University Press, 1969.
LORENZ, Jan et al. How social influence can undermine the wisdom of crowd effect. Proceedings of the National Academy of Sciences, Washington, v. 108, p. 9020-9025, 2011.
LYONS, Russell. The spread of evidence-poor medicine via flawed social-network analysis. Statistics, Politics and Policy, Berlin, v. 2, n. 2, p. 1-29, 2011.
MACY, Michael W.; FLACHE, Andreas. Learning dynamics in social dilemmas. Proceedings of the National Academy of Sciences, Washington, v. 99, p. 7229-7236, 2002.
MAUSS, Marcel. The gift: forms and functions of exchange in archaic societies. London: Routledge, 1922.
ONNELA, Jukka- Pekka et. al. Structure and tie strengths in mobile communication networks. Proceedings of the National Academy of Sciences, Washington, v. 104, n. 18, p. 7332-7336, 2007.
PAOLUCCI, Mario et al. Social knowledge for e-governance: theory and technology of reputation. Rome: ISTC-CNR, 2009.
PUJOL, Josep M. et al. How can social networks ever become complex? modelling the emergence of complex networks from local social exchanges. Journal of Artificial Societies and Social Simulation, Surrey, v. 8, n. 4, 2005.
PUTNAM, Robert. Bowling alone: the collapse and revival of American community. New York: Simon & Schuster, 2001.
PUTTERMAN, Louis. Cooperation and punishment. Science, Washington, v. 328, p. 578- 579, 2010.
RAUB, Werner; WEESIE, Jeroen. Reputation and efficiency in social interactions: an example of network effects. American Journal of Sociology, Chicago, v. 96, p. 626-654, 1990.
RICHERSON, Peter; BOYD, Robert. A dual inheritance model of the human evolutionary process. Journal of Social and Biological Structures, Amsterdam, v. 1, n. 2, p. 127-154, 1978.
RITZER, George (Ed.). Frontiers of social theory: the new syntheses. New York: Columbia University Press, 1990.
ROUCHIER, Juliette; O’CONNOR, Martin; BOUSQUET, François. The creation of a reputation in an artificial society organised by a gift system. Journal of Artificial Societies and Social Simulation, Surrey, v. 4, n. 2, 2001.
SAAM, Nicole J.; HARRER, Andreas. Simulating norms, social inequality, and functional change in artificial societies. Journal of Artificial Societies and Social Simulation, Surrey, v. 2, 1999.
SALMON, Wesley C. Four decades of scientific explanation. Pittsburgh: Pittsburgh University Press, 1989.
SAN MIGUEL, Maxi et al. Challenges in complex systems science. The European Physical Journal Special Topics, Les Ulis, v. 214, n. 245-271, 2012.
SCHELLING, Thomas C. Dynamic models of segregation. Journal of Mathematical Sociology, London, v. 1, p. 143-186, 1971.
SCHOTTER, Andrew. The economic theory of social institutions. Cambridge: Cambridge University Press, 2008.
SHADNAM, Masoud; LAWRENCE, Thomas B. Understanding widespread misconduct in organizations. Business Ethics Quarterly, Charlottesville, v. 21, n. 3, p. 379-407, 2011.
SICHMAN, Jaime S.; CONTE, Rosaria.. Dependence graphs: dependence within and between groups. Computational & Mathematical Organization Theory, Pittsburgh, v. 8, n. 2, p. 87-112, 2002.
SNIJDERS, Tom A. B.; VAN DE BUNT, Gerhard G.; STEGLICH, Christian E. G. Introduction to actor-based models for network dynamics. Social Network, Amsterdam, v. 32, n. 1, p. 44-60, 2010.
SONG, Yang; ZHANG, Lu; GILES, C. Lee. Automatic tag recommendation algorithms for social recommender systems. ACM Transactions on the Web, New York, v. 5, n. 1, 2011.
ALÓS-FERRER, Carlos; KIRCHSTEIGER, Gerog. General equilibrium and the emergence of (non)market clearing trading institutions. Economic Theory, Berlin, v. 44, n. 3, p. 339-360, 2010.
ARTHUR, W. Brian. Out-of-equilibrium economics and agent-based modeling. In: TESFATSION,Leigh; JUDD, Kenneth L. Handbook of computacional economics: agent-based computacional economics. Oxford: Elsevier, 2005. v. 2, p. 1551-1563.
TESFATSION,Leigh; JUDD, Kenneth L. Inductive reasoning and bounded rationality. American Economic Review, Nashville, v. 84, p. 406, 1994.
AXELROD, Robert. The dissemination of culture: a model with local convergence and global polarization. Journal of Conflict Resolution, Newbury Park, v. 41, n. 2, p. 203- 226, 1997.
AXELROD, Robert. The evolution of cooperation. New York: Basic Books, 1984.
AXELROD, Robert. An evolutionary approach to norms. American Political Science Review, Baltimore, v. 80, n. 4, p. 1095-1111, 1986.
AXTELL, Robert L. et al. Population growth and collapse in a multiagent model of the Kayenta Anasazi in Long House Valley. Proceedings of the National Academy of Sciences, Washington, v. 99, p. 7275- 7279, 2002.
BAINBRIDGE, William Sims. The scientific research potential of virtual worlds. Science, Washington, v. 317, n. 5837, p. 472-476, 2007.
BALCAN, Duygu et al. Multiscale mobility networks and the spatial spreading of infectious diseases. Proceedings of the National Academy of Sciences, Washington, v. 106, n. 51, n. 21484-21489, 2009.
BENKLER, Yochai. Coase's penguin, or, linux and the nature of the firm. The Yale Law Journal, Yale, v. 112, n. 3, p. 369-446, 2002.
BICCHIERI, Cristina. The grammar of society: the nature and dynamics of social norms. Cambridge: Cambridge University Press, 2006.
BILLARI, Francesco C. et al. Agent-based computational modelling applications in demography, social, economic and environmental sciences. Heidelberg: Physica Verlag-Springer, 2006.
BORRILL, Paul L.; TESTFATSION, Leigh. Agent-based modeling: the right mathematics for the social sciences? In: DAVIS, Johan B.; HANDS, Wade. The elgar companion to recent economic methodology. New York: Edward Elgar Publishers, 2011. p. 228-258.
BRABHAM, Daren C. Crowdsourcing as a model for problem solving: an introduction and cases. Convergence, London, v. 14, n. 1, p. 75-90, 2008.
CASTELFRANCHI, Cristiano; CONTE, Rosaria. Microsimulation and the social science. Berlin: Springer-Verlag, 1996.
CASTELLO, Xavier et al. Viability and resilience of complex systems: concepts, methods and case studies from ecology and society. New York: Springer-Verlag, 2011.
CATTUTO, Ciro et al. Collective dynamics of social annotation. Proceedings of the National Academy of Sciences, Washington, v. 106, n. 26, p. 10511-10515, 2009.
CEDERMAN, Lars-Erik. Emergent actors in world politics: how states and nations develop. Princeton: Princeton University Press, 1997.
CENTOLA, Damon et al. Homophily, cultural drift, and the co-evolution of cultural groups. Journal of Conflict Resolution, Newbury Park, v. 51, n. 6, p. 905-929, 2007.
CHESNAIS, Jean-Claude. The demographic transition: stages, patterns, and economic implications: a longitudinal study of sixty-seven countries covering the period 1720– 1984. Oxford: Oxford University Press, 1993.
CHRISTAKIS, Nicolas A.; FOWLER, James H. The Spread of Obesity in a Large Social Network over 32 Years. The New England Journal of Medicine, New England, v. 357, p. 370-379, 2007.
CONTE, Rosaria et al. Sociology and social theory in agent based social simulation: a symposium. Computational and Mathematical Organization Theory, Pittsburgh, v. 7, n. 3, p. 183-205, 2001.
CONTE, Rosaria; ANDRIGHETTO, Giulia; CAMPENN, Marco (Ed.). Minding norms. Oxford: Oxford University Press, 2013.
CONTE, Rosaria; PAOLUCCI, Mario. Reputation in artificial societies: social beliefs for social control. Dordrecht: Kluwer, 2002.
DAREMA, Frederica. Grid computing and beyond: the context of dynamic data driven applications systems. Proceedings of the IEEE, New York, v. 93, p. 692-697, 2005.
DENNETT, Daniel C. Descartes error: emotion, reason and the human brain - Damasio, Ar. Times Literary Supplement, 25 ago. 1995. n. 3.
DUNBAR, Robin. The social brain hypothesis. Evolutionary Anthropology: issues, news, and reviews. New York, v. 6, n. 5, p. 178–190, 1998.
EBBERS, Joris J.; WIJNBERG, Nachoem M. Disentangling the effects of reputation and network position on the evolution of alliance networks. Strategic Organization, Thousand Oaks, v. 8, n. 3, p. 255-275, 2010.
EGULUZ, Victor M. et al. Cooperation and the emergence of role differentiation in the dynamics of social networks. American Journal of Sociology, Chicago, v. 110, n. 4, p. 977-1008, 2005.
EHRHARDT, George; MARSILI, Matteo; VEGA-REDONDO, Fernando. Phenomenological models of socioeconomic network dynamics. Physical Review, Melville, v. 74, n. 1, 2006.
EPSTEIN, Joshua M. Agent-based computational models and generative social science. Complexity, New York, v. 4, n. 5, p. 41–60, 1999.
EPSTEIN, Joshua M. Generative social science: studies in agent-based computational modeling. Princeton: Princeton University Press, 2007.
EPSTEIN, Joshua M. Learning to be thoughtless: social norms and individual computation. Computational Economics, Dordrecht, v. 18, p. 9-24, 2001.
EPSTEIN, Joshua M. Modeling civil violence: an agent-based computational approach. Proceedings of the National Academy of Sciences, Washington, v. 99, p. 7243-7250, 2002.
FALCONE, Rino; CASTELFRANCHI, Christiano. Trust theory: a socio-cognitive and computational. Model: Wiley, 2010.
FISHER, Ronald Aylmer. The genetical theory of natural selection. New York: Oxford Universit Press, 1930.
FLACHE, Andreas; MACY, Michael W. Local convergence and global diversity: from interpersonal to social influence. Journal of Conflict Resolution, Newbury Park, v. 55, n. 6, p. 970-995, 2011.
GALÁN, José Manuel et al. Errors and artefacts in agent-based modelling. Journal of Artificial Societies and Social Simulation, Surrey, v. 12, n. 1, 2009.
GAUVIN, Laetitia; VANNIMENUS, Jean; NADAL, Jean-Pierre. Phase diagram of a Schelling segregation model. The European Physical Journal B – Condensed Matter and Complex Systems, Les Ulis, v. 70, n. 2, p. 293-304, 2009.
GIARDINI, Francesca; CONTE, Rosaria. Gossip for social control in natural and artificial societies. Simulation, v. 88, n. 1, p. 18-32, 2012.
GILBERT, Nigel; CONTE, Rosaria (Ed.). Artificial societies: the computer simulation of social life. London: University College London Press, 1995.
GILBERT, Nigel; CONTE, Rosaria (Ed.). Artificial societies: the computer simulation of social life. London: University College London Press, 1995.
GINTIS, Herbert. The bounds of reason. Princeton: Princeton University Press, 2009.
GOLDER, Scott A.; HUBERMAN, Bernardo A. Usage patterns of collaborative tagging systems. Journal of Information Science, Cambridge, v. 32, p. 198-208, 2006.
GONZÁLEZ-AVELLA, Juan Carlos et al. Information feedback and mass media effects in cultural dynamics. Journal of Artificial Societies and Social Simulation, Surrey, v. 10, n. 3, 2007.
GRUJIC, Jelena et al. Social experiments in the mesoscale: humans playing a spatial prisoner's dilemma. PLoS ONE, San Francisco, v. 5, 2010.
HABIB, Laurence; LINE, Wittek. The portfolio as artifact and actor. Mind, Culture Activity, La Jolla, v. 14, n. 4, p. 266-282, 2007.
HAVLIN, Sales et al. Challenges in network science: applications to infrastructures, climate, social systems and economics. The European Physical Journal Special Topics, Les Ulis, v. 214, p. 273-293, 2012.
HELBING, Dirk et al. FuturICT: participatory computing to understand and manage our complex world in a more sustainable and resilient way. The European Physical Journal Special Topics, Heidelberg, v. 214, p. 11-39, 2012.
HELBING, Dirk. Pluralistic modeling of complex systems. Science and Culture, Calcutta, v. 76, p. 315-329, 2010.
HELBING, Dirk; BALIETTI, Stefano. From social data mining to forecasting socioeconomic crise. European Physical Journal: Special Topics, Heidelberg, v. 195, p. 3-68, 2011.
HELBING, Dirk; JOST, Jürgen; LANE, David. Social systems and complexity. Advances in Complex Systems, Amsterdam, v.11, n. 4, p. 485-486, 2008.
HELBING, Dirk; YU, Wenjian; RAUHUT, Heiko. Self-organization and emergence in social systems: modeling the coevolution of social environments and cooperative behavior. The Journal of Mathematical Sociology, London, v. 35, n. 1-3, p. 177-208, 2011.
HENRICH, Joseph et al. Markets, religion, community size, and the evolution of fairness and punishment. Science, Washington, v. 327, p. 1480-1484, 2010.
HUBER, George P. Organizational learning: the contributing processes and the literatures. Organization Science, Providence, v. 2, n. 1, p. 88-115, 1991.
KARSAI, Marton et al. Small but slow world: How network topology and burstiness slow down spreading. Physical Review, New York, v. 83, n. 2, p. 1-4, 2011.
KITTUR, Aniket. Crowdsourcing user studies with mechanical turk.In: ANNUAL SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, 36., 2008, New York. Proceedings… New York: ACM, 2008.
KIUKKONEN, N. et al. Proceedings of international conference on pervasive services. Berlin: ACM, 2010.
LANE, Nicholas D. et al. A survey of mobile phone sensing. IEEE Communications Magazine, New York, v. 48, n. 9, p. 140-150, 2010.
LAZER, David et al. Computation social science. Science, Washington, v. 323, p. 721-724, 2009.
LEWIS, David. Convention: a philosophical study. Harvard: Harvard University Press, 1969.
LORENZ, Jan et al. How social influence can undermine the wisdom of crowd effect. Proceedings of the National Academy of Sciences, Washington, v. 108, p. 9020-9025, 2011.
LYONS, Russell. The spread of evidence-poor medicine via flawed social-network analysis. Statistics, Politics and Policy, Berlin, v. 2, n. 2, p. 1-29, 2011.
MACY, Michael W.; FLACHE, Andreas. Learning dynamics in social dilemmas. Proceedings of the National Academy of Sciences, Washington, v. 99, p. 7229-7236, 2002.
MAUSS, Marcel. The gift: forms and functions of exchange in archaic societies. London: Routledge, 1922.
ONNELA, Jukka- Pekka et. al. Structure and tie strengths in mobile communication networks. Proceedings of the National Academy of Sciences, Washington, v. 104, n. 18, p. 7332-7336, 2007.
PAOLUCCI, Mario et al. Social knowledge for e-governance: theory and technology of reputation. Rome: ISTC-CNR, 2009.
PUJOL, Josep M. et al. How can social networks ever become complex? modelling the emergence of complex networks from local social exchanges. Journal of Artificial Societies and Social Simulation, Surrey, v. 8, n. 4, 2005.
PUTNAM, Robert. Bowling alone: the collapse and revival of American community. New York: Simon & Schuster, 2001.
PUTTERMAN, Louis. Cooperation and punishment. Science, Washington, v. 328, p. 578- 579, 2010.
RAUB, Werner; WEESIE, Jeroen. Reputation and efficiency in social interactions: an example of network effects. American Journal of Sociology, Chicago, v. 96, p. 626-654, 1990.
RICHERSON, Peter; BOYD, Robert. A dual inheritance model of the human evolutionary process. Journal of Social and Biological Structures, Amsterdam, v. 1, n. 2, p. 127-154, 1978.
RITZER, George (Ed.). Frontiers of social theory: the new syntheses. New York: Columbia University Press, 1990.
ROUCHIER, Juliette; O’CONNOR, Martin; BOUSQUET, François. The creation of a reputation in an artificial society organised by a gift system. Journal of Artificial Societies and Social Simulation, Surrey, v. 4, n. 2, 2001.
SAAM, Nicole J.; HARRER, Andreas. Simulating norms, social inequality, and functional change in artificial societies. Journal of Artificial Societies and Social Simulation, Surrey, v. 2, 1999.
SALMON, Wesley C. Four decades of scientific explanation. Pittsburgh: Pittsburgh University Press, 1989.
SAN MIGUEL, Maxi et al. Challenges in complex systems science. The European Physical Journal Special Topics, Les Ulis, v. 214, n. 245-271, 2012.
SCHELLING, Thomas C. Dynamic models of segregation. Journal of Mathematical Sociology, London, v. 1, p. 143-186, 1971.
SCHOTTER, Andrew. The economic theory of social institutions. Cambridge: Cambridge University Press, 2008.
SHADNAM, Masoud; LAWRENCE, Thomas B. Understanding widespread misconduct in organizations. Business Ethics Quarterly, Charlottesville, v. 21, n. 3, p. 379-407, 2011.
SICHMAN, Jaime S.; CONTE, Rosaria.. Dependence graphs: dependence within and between groups. Computational & Mathematical Organization Theory, Pittsburgh, v. 8, n. 2, p. 87-112, 2002.
SNIJDERS, Tom A. B.; VAN DE BUNT, Gerhard G.; STEGLICH, Christian E. G. Introduction to actor-based models for network dynamics. Social Network, Amsterdam, v. 32, n. 1, p. 44-60, 2010.
SONG, Yang; ZHANG, Lu; GILES, C. Lee. Automatic tag recommendation algorithms for social recommender systems. ACM Transactions on the Web, New York, v. 5, n. 1, 2011.
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2013-03-23
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CONTE, Rosaria et al. Manifesto of computacional social science. Mediações - Revista de Ciências Sociais, Londrina, v. 18, n. 1, p. 20–54, 2013. DOI: 10.5433/2176-6665.2013v18n1p20. Disponível em: https://ojs.uel.br/revistas/uel/index.php/mediacoes/article/view/16806. Acesso em: 21 nov. 2024.
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