skip to main content
research-article
Public Access

Social Networks under Stress: Specialized Team Roles and Their Communication Structure

Published:08 February 2019Publication History
Skip Abstract Section

Abstract

Social network research has begun to take advantage of fine-grained communications regarding coordination, decision-making, and knowledge sharing. These studies, however, have not generally analyzed how external events are associated with a social network’s structure and communicative properties. Here, we study how external events are associated with a network’s change in structure and communications. Analyzing a complete dataset of millions of instant messages among the decision-makers with different roles in a large hedge fund and their network of outside contacts, we investigate the link between price shocks, network structure, and change in the affect and cognition of decision-makers embedded in the network. We also analyze the communication dynamics among specialized teams in the organization. When price shocks occur the communication network tends not to display structural changes associated with adaptiveness such as the activation of weak ties to obtain novel information. Rather, the network “turtles up.” It displays a propensity for higher clustering, strong tie interaction, and an intensification of insider vs. outsider and within-role vs. between-role communication. Further, we find changes in network structure predict shifts in cognitive and affective processes, execution of new transactions, and local optimality of transactions better than prices, revealing the important predictive relationship between network structure and collective behavior within a social network.

References

  1. Lada Adamic and Eytan Adar. 2005. How to search a social network. Soc. Netw. 27, 3 (2005), 187--203.Google ScholarGoogle ScholarCross RefCross Ref
  2. Sumit Agarwal, Ran Duchin, and Denis Sosyura. 2012. In the mood for a loan: The causal effect of sentiment on credit origination. (2012). SSRN: https://ssrn.com/abstract=2141030 orGoogle ScholarGoogle Scholar
  3. Yong-Yeol Ahn, Seungyeop Han, Haewoon Kwak, Sue Moon, and Hawoong Jeong. 2007. Analysis of topological characteristics of huge online social networking services. In Proceedings of the 16th International Conference on World Wide Web. ACM, 835--844. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Alok Bhargava, Luisa Franzini, and Wiji Narendranathan. 1982. Serial correlation and the fixed effects model. Rev. Econ. Stud. 49, 4 (1982), 533--549.Google ScholarGoogle ScholarCross RefCross Ref
  5. Daniel J. Brass, Joseph Galaskiewicz, Henrich R. Greve, and Wenpin Tsai. 2004. Taking stock of networks and organizations: A multilevel perspective. Acad. Manage. J. 47, 6 (2004), 795--817.Google ScholarGoogle Scholar
  6. Ronald S. Burt. 2009. Structural Holes: The Social Structure of Competition. Harvard University Press.Google ScholarGoogle Scholar
  7. Carter T. Butts, Miruna Petrescu-Prahova, and B. Remy Cross. 2007. Responder communication networks in the World Trade Center disaster: Implications for modeling of communication within emergency settings. Math. Sociol. 31, 2 (2007), 121--147.Google ScholarGoogle ScholarCross RefCross Ref
  8. Deepayan Chakrabarti and Christos Faloutsos. 2012. Graph mining: Laws, tools, and case studies. Synth. Lect. Data Min. Knowl. Discov. 7, 1 (2012), 1--207. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. James S. Coleman. 1988. Social capital in the creation of human capital. Am. J. Sociol. 94 (1988), S95--S120.Google ScholarGoogle ScholarCross RefCross Ref
  10. Lorenzo Coviello, Yunkyu Sohn, Adam D. I. Kramer, Cameron Marlow, Massimo Franceschetti, Nicholas A. Christakis, and James H. Fowler. 2014. Detecting emotional contagion in massive social networks. PLoS ONE 9, 3 (2014), e90315.Google ScholarGoogle ScholarCross RefCross Ref
  11. Munmun De Choudhury, Winter A. Mason, Jake M. Hofman, and Duncan J. Watts. 2010. Inferring relevant social networks from interpersonal communication. In Proceedings of the 19th International Conference on World Wide Web. ACM, 301--310. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jana Diesner, Terrill L. Frantz, and Kathleen M. Carley. 2005. Communication networks from the Enron email corpus? It’s always about the people. Enron is no different? Comput. Math. Organiz. Theory 11, 3 (2005), 201--228. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Peter Sheridan Dodds, Duncan J. Watts, and Charles F. Sabel. 2003. Information exchange and the robustness of organizational networks. Proc. Natl. Acad. Sci. U.S.A. 100, 21 (2003), 12516--12521.Google ScholarGoogle ScholarCross RefCross Ref
  14. James Durbin and Geoffrey S. Watson. 1951. Testing for serial correlation in least squares regression. II. Biometrika 38, 1/2 (1951), 159--177.Google ScholarGoogle ScholarCross RefCross Ref
  15. Sunasir Dutta and Hayagreeva Rao. 2015. Infectious diseases, contamination rumors and ethnic violence: Regimental mutinies in the Bengal Native Army in 1857 India. Organiz. Behav. Hum. Decision Process. 129 (2015), 36--47.Google ScholarGoogle ScholarCross RefCross Ref
  16. David Easley and Jon Kleinberg. 2010. Networks, Crowds, and Markets: Reasoning about a Highly Connected World. Cambridge University Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Aleksander P. J. Ellis. 2006. System breakdown: The role of mental models and transactive memory in the relationship between acute stress and team performance. Acad. Manage. J. 49, 3 (2006), 576--589.Google ScholarGoogle ScholarCross RefCross Ref
  18. Mark Fenton-O’Creevy, Emma Soane, Nigel Nicholson, and Paul Willman. 2011. Thinking, feeling and deciding: The influence of emotions on the decision making and performance of traders. J. Organiz. Behav. 32, 8 (2011), 1044--1061.Google ScholarGoogle ScholarCross RefCross Ref
  19. Murray Gell-Mann and Seth Lloyd. 1996. Information measures, effective complexity, and total information. Complexity 2, 1 (1996), 44--52. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Clark G. Gilbert. 2005. Unbundling the structure of inertia: Resource versus routine rigidity. Acad. Manage. J. 48, 5 (2005), 741--763.Google ScholarGoogle ScholarCross RefCross Ref
  21. Mark Granovetter. 1985. Economic action and social structure: The problem of embeddedness. Am. J. Sociol. 91, 3 (1985), 481--510.Google ScholarGoogle ScholarCross RefCross Ref
  22. Mark S. Granovetter. 1973. The strength of weak ties. Am. J. Sociol. 78, 6 (1973), 1360--1380.Google ScholarGoogle ScholarCross RefCross Ref
  23. Matthew O. Jackson. 2010. Social and Economic Networks. Princeton University Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Daniel Kahneman. 2011. Thinking, Fast and Slow. Macmillan.Google ScholarGoogle Scholar
  25. Qing Ke and Yong-Yeol Ahn. 2014. Tie strength distribution in scientific collaboration networks. Phys. Rev. E 90, 3 (2014), 032804.Google ScholarGoogle ScholarCross RefCross Ref
  26. Martin Kilduff and Daniel J. Brass. 2010. Organizational social network research: Core ideas and key debates. Acad. Manage. Ann. 4, 1 (2010), 317--357.Google ScholarGoogle ScholarCross RefCross Ref
  27. Bryan Klimt and Yiming Yang. 2004. The enron corpus: A new dataset for email classification research. In Machine Learning: ECML 2004 (ECML'04). Lecture Notes in Computer Science, Vol 3201. Springer, Berlin, Heidelberg. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Gueorgi Kossinets, Jon Kleinberg, and Duncan Watts. 2008. The structure of information pathways in a social communication network. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 435--443. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Gueorgi Kossinets and Duncan J. Watts. 2006. Empirical analysis of an evolving social network. Science 311, 5757 (2006), 88--90.Google ScholarGoogle Scholar
  30. Adam D. I. Kramer, Jamie E. Guillory, and Jeffrey T. Hancock. 2014. Experimental evidence of massive-scale emotional contagion through social networks. Proc. Natl Acad. Sci. U.S.A. 111, 24 (2014), 8788--8790.Google ScholarGoogle ScholarCross RefCross Ref
  31. David Lazer, Alex Sandy Pentland, Lada Adamic, Sinan Aral, Albert Laszlo Barabasi, Devon Brewer, Nicholas Christakis, Noshir Contractor, James Fowler, Myron Gutmann, et al. 2009. Life in the network: The coming age of computational social science. Science 323, 5915 (2009), 721.Google ScholarGoogle Scholar
  32. Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. 2007. Graph evolution: Densification and shrinking diameters. ACM Trans. Knowl. Discov. Data 1, 1 (2007), 2. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Andrew W. Lo and Dmitry V. Repin. 2002. The psychophysiology of real-time financial risk processing. J. Cogn. Neurosci. 14, 3 (2002), 323--339. Google ScholarGoogle ScholarDigital LibraryDigital Library
  34. Burton G. Malkiel and Eugene F. Fama. 1970. Efficient capital markets: A review of theory and empirical work. J. Finance 25, 2 (1970), 383--417.Google ScholarGoogle ScholarCross RefCross Ref
  35. Tanya Menon and Edward Bishop Smith. 2014. Identities in flux: Cognitive network activation in times of change. Soc. Sci. Res. 45 (2014), 117--130.Google ScholarGoogle ScholarCross RefCross Ref
  36. Mark Newman. 2010. Networks: An Introduction. Oxford University Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Mark Newman, Albert-Laszlo Barabasi, and Duncan J. Watts. 2011. The Structure and Dynamics of Networks. Princeton University Press. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. Mark E. J. Newman. 2003. The structure and function of complex networks. SIAM Rev. 45, 2 (2003), 167--256.Google ScholarGoogle ScholarDigital LibraryDigital Library
  39. Mark E. J. Newman. 2006. Modularity and community structure in networks. Proc. Natl. Acad. Sci. U.S.A. 103, 23 (2006), 8577--8582.Google ScholarGoogle ScholarCross RefCross Ref
  40. Leto Peel and Aaron Clauset. 2015. Detecting change points in the large-scale structure of evolving networks. In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI'15). AAAI Press, 2914--2920. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. Charles Perrow. 2011. Normal Accidents: Living with High Risk Technologies. Princeton University Press.Google ScholarGoogle ScholarCross RefCross Ref
  42. E. Platt and D. M. Romero. 2018. Network structure, efficiency, and performance in WikiProjects. In Proceedings of International AAAI Conference on Web and Social Media (ICWSM’18).Google ScholarGoogle Scholar
  43. Walter Powell. 1990. Neither market nor hierarchy: Network forms of organization. Res. Organ. Behav. 12 (1990), 295--336.Google ScholarGoogle Scholar
  44. Tobias Preis, Helen Susannah Moat, and H. Eugene Stanley. 2013. Quantifying trading behavior in financial markets using Google Trends. Sci. Rep. 3, Article 1684 (2013), 01684.Google ScholarGoogle Scholar
  45. Daniel M. Romero, Roderick I. Swaab, Brian Uzzi, and Adam D. Galinsky. 2015. Mimicry is presidential: Linguistic style matching in presidential debates and improved polling numbers. Pers. Soc. Psychol. Bull. 41, 10 (2015), 1311--1319.Google ScholarGoogle ScholarCross RefCross Ref
  46. Daniel M. Romero, Brian Uzzi, and Jon Kleinberg. 2016. Social networks under stress. In Proceedings of the 25th International Conference on World Wide Web. International World Wide Web Conferences Steering Committee, 9--20. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Serguei Saavedra, Kathleen Hagerty, and Brian Uzzi. 2011. Synchronicity, instant messaging, and performance among financial traders. Proc. Natl. Acad. Sci. U.S.A. 108, 13 (2011), 5296--5301.Google ScholarGoogle ScholarCross RefCross Ref
  48. Serguei Saavedra, R. Dean Malmgren, Nicholas Switanek, and Brian Uzzi. 2013. Foraging under conditions of short-term exploitative competition: The case of stock traders. Proc. R. Soc. B 280, 1755 (2013) 2012--2901.Google ScholarGoogle ScholarCross RefCross Ref
  49. Serguei Saavedra, Felix Reed-Tsochas, and Brian Uzzi. 2008. Asymmetric disassembly and robustness in declining networks. Proc. Natl. Acad. Sci. U.S.A. 105, 43 (2008), 16466--16471.Google ScholarGoogle ScholarCross RefCross Ref
  50. Edward Bishop Smith, Tanya Menon, and Leigh Thompson. 2012. Status differences in the cognitive activation of social networks. Organiz. Sci. 23, 1 (2012), 67--82. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. Barry M. Staw, Lance E. Sandelands, and Jane E. Dutton. 1981. Threat rigidity effects in organizational behavior: A multilevel analysis. Admin. Sci. Quart. 26, 4 (1981), 501--524.Google ScholarGoogle ScholarCross RefCross Ref
  52. Yla R. Tausczik and James W. Pennebaker. 2010. The psychological meaning of words: LIWC and computerized text analysis methods. J. Lang. Soc. Psychol. 29, 1 (2010), 24--54.Google ScholarGoogle ScholarCross RefCross Ref
  53. Paul C. Tetlock. 2007. Giving content to investor sentiment: The role of media in the stock market. J. Finance 62, 3 (2007), 1139--1168.Google ScholarGoogle ScholarCross RefCross Ref
  54. Brian Uzzi. 1996. The sources and consequences of embeddedness for the economic performance of organizations: The network effect. Am. Sociol. Rev. 61, 4 (1996), 674--698.Google ScholarGoogle ScholarCross RefCross Ref
  55. Bimal Viswanath, Alan Mislove, Meeyoung Cha, and Krishna P. Gummadi. 2009. On the evolution of user interaction in facebook. In Proceedings of the 2nd ACM Workshop on Online Social Networks. ACM, 37--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Lilian Weng, Jacob Ratkiewicz, Nicola Perra, Bruno Gonçalves, Carlos Castillo, Francesco Bonchi, Rossano Schifanella, Filippo Menczer, and Alessandro Flammini. 2013. The role of information diffusion in the evolution of social networks. In Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM, 356--364. Google ScholarGoogle ScholarDigital LibraryDigital Library
  57. Robert E. Whaley. 2000. The investor fear gauge. J. Portf. Manage. 26, 3 (2000), 12--17.Google ScholarGoogle ScholarCross RefCross Ref
  58. Ark Fangzhou Zhang, Livneh Danielle, Ceren Budak, Lionel P. Robert Jr., and Daniel M. Romero. 2017. Shocking the crowd: The effect of censorship shocks on Chinese Wikipedia. In Proceedings of the 11th International AAAI Conference on Web and Social Media.Google ScholarGoogle Scholar

Index Terms

  1. Social Networks under Stress: Specialized Team Roles and Their Communication Structure

              Recommendations

              Comments

              Login options

              Check if you have access through your login credentials or your institution to get full access on this article.

              Sign in

              Full Access

              • Published in

                cover image ACM Transactions on the Web
                ACM Transactions on the Web  Volume 13, Issue 1
                February 2019
                206 pages
                ISSN:1559-1131
                EISSN:1559-114X
                DOI:10.1145/3297729
                Issue’s Table of Contents

                Copyright © 2019 ACM

                Publisher

                Association for Computing Machinery

                New York, NY, United States

                Publication History

                • Published: 8 February 2019
                • Accepted: 1 November 2018
                • Revised: 1 August 2018
                • Received: 1 August 2017
                Published in tweb Volume 13, Issue 1

                Permissions

                Request permissions about this article.

                Request Permissions

                Check for updates

                Qualifiers

                • research-article
                • Research
                • Refereed

              PDF Format

              View or Download as a PDF file.

              PDF

              eReader

              View online with eReader.

              eReader
              About Cookies On This Site

              We use cookies to ensure that we give you the best experience on our website.

              Learn more

              Got it!