Installing computational social science: Facing the challenges of new information and communication technologies in social science

Methodological Innovations

Volumn 9, Issue , 2016, Pages

  Heiberger, Raphael H ^a   Riebling, Jan R ^b  

^a UNIVERSITY OF BREMEN   (Germany)

^b UNIVERSITY OF BAMBERG   (Germany)

Author keywords

Computational social science; data management; Python; R; research practices; theory development

Indexed keywords

EID: 85038436190     PISSN: None     EISSN: 20597991     Source Type: Journal    
DOI: 10.1177/2059799115622763     Document Type: Article

References (72)

1. Bail CA, (2012) The Fringe Effect Civil Society Organizations and the evolution of media discourse about Islam since the September 11th attacks. American Sociological Review 77: 855–879.
2. Bail CA, (2014) The cultural environment: Measuring culture with big data. Theory and Society 43: 465–482.
3. Bailey KD, (1994) Sociology and the New Systems Theory: Toward a Theoretical Synthesis. Albany, NY: SUNY Press.
4. Bird S, Klein E, Loper E, (2009) Natural Language Processing with Python—Analyzing Text with the Natural Language Toolkit. Sebastopol, CA: O’Reilly Media.
5. Bourdieu P, (1977) Outline of a Theory of Practice. Cambridge, UK: Cambridge University Press.
6. Brandes U, (2001) A faster algorithm for betweenness centrality. Journal of Mathematical Sociology 25: 163–177.
7. Buldyrev SV, Parshani R, Paul G, et al. (2010) Catastrophic cascade of failures in interdependent networks. Nature 464: 1025–1028.
8. Burrows R, Savage M, (2014) After the crisis? Big Data and the methodological challenges of empirical sociology. Big Data & Society 1: 1–6.
9. Burt RS, (1995) Structural Holes: The Social Structure of Competition (reprint edition). Cambridge, MA: Harvard University Press.
10. Chevaleyre Y, Endriss U, Lang J, et al. (2007) A short introduction to computational social choice. In: van Leeuwen J, Italiano GF, van der Hoek W, et al. (eds) SOFSEM 2007: Theory and Practice of Computer Science. Berlin, Heidelberg: Springer, pp. 51–69.
11. Cioffi-Revilla C, (2014) Introduction to Computational Social Science (Texts in Computer Science). London: Springer.
12. Conte R, Edmonds B, Moss S, et al. (2001) Sociology and social theory in agent based social simulation: A symposium. Computational & Mathematical Organization Theory 7: 183–205.
13. Conte R, Gilbert N, Bonelli G, et al. (2012) Manifesto of computational social science. European Physical Journal: Special Topics 214: 325–346.
14. De Vaan M, Stark D, Vedres B, (2015) Game changer: The topology of creativity. American Journal of Sociology 120: 1144–1194.
15. Deerwester S, Dumais ST, Furnas GW, et al. (1990) Indexing by latent semantic analysis. Journal of the American Society for Information Science 41: 391–407.
16. Diekmann A, Jann B, Przepiorka W, et al. (2014) Reputation formation and the evolution of cooperation in anonymous online markets. American Sociological Review 79: 65–85.
17. Downey A, (2012) Think Python: How to Think Like a Computer Scientist. Sebastopol, CA: O’Reilly Media.
18. Dumbill E, (2012) What Is Big Data? O’Reilly Media. Available at: https://beta.oreilly.com/ideas/what-is-big-data (accessed 3 August 2015).
19. Feinerer I, Hornik K, Meyer D, (2008) Text mining infrastructure in R. Journal of Statistical Software 25: 1–54.
20. Fligstein N, McAdam D, (2012) A Theory of Fields. New York: Oxford University Press.
21. Freeman LC, (2011) The development of social network analysis—With an emphasis on recent events. In: Scott J, Carrington PJ, (eds) The SAGE Handbook of Social Network Analysis. London: SAGE, pp. 26–54.
22. Freeman LC, Webster CM, (1994) Interpersonal proximity in social and cognitive space. Social Cognition 12: 223–247.
23. Friedkin NE, (1986) A formal theory of social power. Journal of Mathematical Sociology 12: 103–126.
24. Giles J, (2012) Computational social science: Making the links. Nature News 488: 448.
25. Girvan M, Newman ME, (2002) Community structure in social and biological networks. Proceedings of the National Academy of Sciences 99: 7821–7826.
26. Goel S, Hofman JM, Lahaie S, et al. (2010) Predicting consumer behavior with Web search. PNAS 107: 17486–17490.
27. Golder SA, Macy MW, (2011) Diurnal and seasonal mood vary with work, sleep, and daylength across diverse cultures. Science 333: 1878–1881.
28. Hagberg AA, Schult DA, Swart PJ, (2008) Exploring network structure, dynamics, and function using NetworkX. In: Varoquaux G, Vaught T, Millman J, (eds) Proceedings of the 7th Python in Science Conference (SciPy2008): Presented at the SciPy2008. Pasadena, CA, pp. 11–15. Available at: http://conference.scipy.org/proceedings/scipy2008/paper_2/
29. Harrington A, (2005) Modern Social Theory. Oxford: Oxford University Press.
30. Heiberger RH, (2014) Stock network stability in times of crisis. Physica A: Statistical Mechanics and its Applications 393: 376–381.
31. Heiberger RH, (2015) Collective attention and stock prices: Evidence from Google Trends Data on Standard and Poor’s 100. PLoS ONE 10: e0135311.
32. Heiberger RH, Riebling J, (2015) U.S. and whom? Structures and communities of international economic research. Journal of Social Structure 16: 1–12.
33. Helbing D, (2012) Introduction: The FuturICT knowledge accelerator towards a more resilient and sustainable future. European Physical Journal: Special Topics 214: 5–9.
34. Herndon T, Ash M, Pollin R, (2014) Does high public debt consistently stifle economic growth? A critique of Reinhart and Rogoff. Cambridge Journal of Economics 38: 257–279.
35. Homans GC, (2003) The Human Group. New Brunswick, NJ: Transaction Publishers.
36. Isaac AG, (2008) Simulating evolutionary games: A Python-based introduction. Journal of Artificial Societies and Social Simulation 11: 8.
37. Kalberg S, (1980) Max Weber’s types of rationality: Cornerstones for the analysis of rationalization processes in history. American Journal of Sociology 85: 1145–1179.
38. Karsai M, Kivelä M, Pan RK, et al. (2011) Small but slow world: How network topology and burstiness slow down spreading. Physical Review E 83: 025102.
39. Kerzner M, Maniyam S, (2013) Hadoop Illuminated. Hadoop Illuminated LLC. Available at: http://hadoopilluminated.com/hadoop_illuminated/hadoop-illuminated.pdf
40. King G, (2011) Ensuring the data-rich future of the social sciences. Science 331: 719–721.
41. Kitano H, (2002) Computational systems biology. Nature 420: 206–210.
42. Kroneberg C, Kalter F, (2012) Rational choice theory and empirical research: Methodological and theoretical contributions in Europe. Annual Review of Sociology 38: 73–92.
43. Lazer D, Kennedy R, King G, et al. (2014) The parable of Google Flu: Traps in Big Data analysis. Science 343: 1203–1205.
44. Lazer D, Pentland A, Adamic L, et al. (2009) Computational Social Science. Science 323: 721–723.
45. Lehmann TC, Rolfsen JA, Clark TD, (2015) Predicting the trajectory of the evolving international cyber regime: Simulating the growth of a social network. Social Networks 41: 72–84.
46. Lewis K, Kaufman J, Gonzalez M, et al. (2008) Tastes, ties, and time: A new social network dataset using Facebook.com. Social Networks 30: 330–342.
47. Luhmann N, (1990) Essays on Self-Reference. New York: Columbia University Press.
48. Lutter M, (2015) Do women suffer from network closure? The moderating effect of social capital on gender inequality in a project-based labor market, 1929 to 2010. American Sociological Review 80: 329–358.
49. McCullough BD, (2010) Econometric computing with R. In: Vinod HD, (ed.) Advances in Social Science Research Using R. New York: Springer, pp. 1–21.
50. Maturana HR, Varela F, (eds) (1973) Autopoiesis and Cognition: The Realization of the Living. Dordrecht: D. Reidel.
51. May RM, Levin SA, Sugihara G, (2008) Complex systems: Ecology for bankers. Nature 451: 893–895.
52. Milgram S, (1967) The small world problem. Psychology Today 2: 60–67.
53. Onnela J-P, Saramäki J, Hyvönen J, et al. (2007) Structure and tie strengths in mobile communication networks. PNAS 104: 7332–7336.
54. Peixoto TP, (2015) graph-tool: Efficient network analysis with python. Available at: https://graph-tool.skewed.de/ (accessed 29 July 2015).
55. Qin X, Cunningham P, Salter-Townshend M, (2015) The influence of network structures of Wikipedia discussion pages on the efficiency of WikiProjects. Social Networks 43: 1–15.
56. Rehurek R, Sojka P, (2010) Software framework for topic modelling with large corpora. In: Proceedings of the LREC 2010 workshop on new challenges for NLP frameworks, 22 May, pp. 45–50. Malta: ELRAValetta.
57. Reinhart CM, Rogoff KS, (2011) The forgotten history of domestic debt. The Economic Journal 121: 319–350.
58. Ruths D, Pfeffer J, (2014) Social media for large studies of behavior. Science 346: 1063–1064.
59. Savage M, Burrows R, (2007) The coming crisis of empirical sociology. Sociology 41: 885–899.
60. Schweitzer F, Fagiolo G, Sornette D, et al. (2009) Economic networks: The new challenges. Science 325: 422.
61. Scott J, Carrington PJ, (2011) The SAGE handbook of social network analysis. Los Angeles, CA: SAGE.
62. Simon HA, (1982) Models of Bounded Rationality: Empirically Grounded Economic Reason. Cambridge, MA: MIT Press.
63. Star SL, (1989) The structure of Ill-structured solutions: Boundary objects and heterogeneous problem solving. In: Gasser LM, Huhns N, (eds) Distributed Artificial Intelligence. London: Pitman, pp. 37–54.
64. Steane A, (1998) Quantum computing. Reports on Progress in Physics 61: 117–173.
65. Von Foerster H, (2007) Understanding Understanding: Essays on Cybernetics and Cognition. New York: Springer Science + Business Media.
66. Uprichard E, (2013) Big Data, Little Questions? Discover Society. Available at: http://www.discoversociety.org/focus-big-data-little-questions (accessed 11 January 2016).
67. Wassermann S, Faust K, (1994) Social Network Analysis: Methods and Applications. Cambridge, MA: Cambridge University Press.
68. Watts DJ, (2004) The “New” science of networks. Annual Review of Sociology 30: 243–270.
69. Watts DJ, (2014) Common sense and sociological explanations. American Journal of Sociology 120: 313–351.
70. Watts DJ, Strogatz SH, (1998) Collective dynamics of “small-world” networks. Nature 393: 440–442.
71. Wild F, (2015) LAS: Latent Semantic Analysis. Available at: https://cran.r-project.org/web/packages/lsa/index.html
72. Wimmer A, Lewis K, (2010) Beyond and below racial homophily: ERG models of a friendship network documented on Facebook. American Journal of Sociology 116: 583–642.