skip to main content
10.1145/1531674.1531684acmconferencesArticle/Chapter ViewAbstractPublication PagesgroupConference Proceedingsconference-collections
research-article

Effects of feedback and peer pressure on contributions to enterprise social media

Published:10 May 2009Publication History

ABSTRACT

Increasingly, large organizations are experimenting with internal social media (e.g., blogs, forums) as a platform for widespread distributed collaboration. Contributions to their counterparts outside the organization's firewall are driven by attention from strangers, in addition to sharing among friends. However, employees in a workplace under time pressures may be reluctant to participate and the audience for their contributions is comparatively smaller. Participation rates also vary widely from group to group. So what influences people to contribute in this environment?

In this paper, we present the results of a year-long empirical study of internal social media participation at a large technology company, and analyze the impact attention, feedback, and managers' and coworkers' participation have on employees' behavior. We find feedback in the form of posted comments is highly correlated with a user's subsequent participation. Recent manager and coworker activity relate to users initiating or resuming participation in social media. These findings extend, to an aggregate level, the results from prior interviews about blogging at the company and offer design and policy implications for organizations seeking to encourage social media adoption.

References

  1. A. Anagnostopoulos, R. Kumar, and M. Mahdian. Influence and correlation in social networks. In KDD '08: Proc. of the 14th ACM int'l conf. on Knowledge discovery and data mining, pages 7--15, New York, NY, USA, 2008. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. J. Arguello, B. S. Butler, E. Joyce, R. Kraut, K. S. Ling, C. Rosé, and X. Wang. Talk to me: foundations for successful individual-group interactions in online communities. In CHI '06: Proc. of the ACM conf. on Human Factors in computing systems, pages 959--968, New York, NY, USA, 2006. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. G. Beenen, K. Ling, X. Wang, K. Chang, D. Frankowski, P. Resnick, and R. E. Kraut. Using social psychology to motivate contributions to online communities. In CSCW '04: Proc. of the ACM conf. on Computer supported cooperative work, pages 212--221, New York, NY, USA, 2004. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Y. Benkler. Coase's penguin, or linux and the nature of the firm. The Yale Law Journal, 112:369--446, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  5. G. Box and D. R. Cox. An analysis of transformations. J. of the Royal Statistical Society, B(26):211--252, 1964.Google ScholarGoogle Scholar
  6. Y. Bramoulle, H. Djebbari, and B. Fortin. Identification of peer effects through social networks. Technical report, University of Laval, 2006.Google ScholarGoogle Scholar
  7. M. Burke and R. Kraut. Mind your ps and qs: the impact of politeness and rudeness in online communities. In CSCW '08: Proc. of the ACM conf. on Computer supported cooperative work, pages 281--284, New York, NY, USA, 2008. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. B. Butler, L. Sproull, S. Kiesler, and R. Kraut. Community effort in online groups: Who does the work and why? In S. Weisband and L. Atwater, editors, Leadership at a Distance. Erlbaum, 2002.Google ScholarGoogle Scholar
  9. P. R. Cohen. Empirical Methods for Artificial Intelligence. MIT Press, Cambridge, MA, 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. D. Collett. Modelling Binary Data. CRC Press, Boca Raton, FL, 2nd edition, 2003.Google ScholarGoogle Scholar
  11. D. Crandall, D. Cosley, D. Huttenlocher, J. Kleinberg, and S. Suri. Feedback effects between similarity and social influence in online communities. In KDD '08: Proc. of the 14th ACM int'l conf. on Knowledge discovery and data mining, pages 160--168, New York, NY, USA, 2008. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. T. H. Davenport and J. C. Beck. The attention economy. Ubiquity, 2(14):1, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. J. DiMicco, D. R. Millen, W. Geyer, C. Dugan, B. Brownholtz, and M. Muller. Motivations for social networking at work. In CSCW '08: Proc. of the ACM conf. on Computer supported cooperative work, pages 711--720, New York, NY, USA, 2008. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. L. Efimova and J. Grudin. Crossing boundaries: A case study of employee blogging. In HICSS '07: Proc. of the 40th Annual Hawaii int'l conf. on System Sciences, page 86, Washington, DC, USA, 2007. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. S. Farrell, T. Lau, S. Nusser, E. Wilcox, and M. Muller. Socially augmenting employee profiles with people-tagging. In UIST '07: Proc. of the 20th annual ACM symposium on User interface software and technology, pages 91--100, New York, NY, USA, 2007. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. J. Grudin. Groupware and social dynamics: eight challenges for developers. Commun.ACM, 37(1):92--105, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. P. J. Hinds and J. Pfeffer. Why organizations don't "know what they know": Cognitive and motivational factors affecting the transfer of expertise. In M. S. Ackerman, V. Pipek, and V. Wulf, editors, Sharing Expertise: Beyond Knowledge Management, pages 3--26. MIT Press, Cambridge, MA, 2003.Google ScholarGoogle Scholar
  18. B. A. Huberman, D. M. Romero, and F. Wu. Crowdsourcing, attention and productivity. CoRR, abs/0809.3030, 2008.Google ScholarGoogle Scholar
  19. B. A. Huberman, D. M. Romero, and F. Wu. Social networks that matter: Twitter under the microscope. First Monday, 14(1), January 2009.Google ScholarGoogle Scholar
  20. J. Huh, L. Jones, T. Erickson, W. A. Kellogg, R. K. E. Bellamy, and J. C. Thomas. Blogcentral: the role of internal blogs at work. In CHI'07: extended abstracts on Human factors in computing systems, pages 2447--2452, New York, NY, USA, 2007. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. A. Jackson, J. Yates, and W. Orlikowski. Corporate blogging: Building community through persistent digital talk. In HICSS '07: Proc. of the 40th Annual Hawaii int'l conf. on System Sciences, page 80, Washington, DC, USA, 2007. IEEE Computer Society. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. P. Kolari, T. Finin, Y. Yesha, Y. Yesha, K. Lyons, S. Perelgut, and J. Hawkins. On the Structure, Properties and Utility of Internal Corporate Blogs. In Proc. of the int'l conf. on Weblogs and Social Media (ICWSM 2007), March 2007.Google ScholarGoogle Scholar
  23. R. E. Kraut, S. R. Fussel, S. E. Brennan, and J. Siegel. Understanding effects of proximity on collaboration: Implications for technologies to support remote collaborative work. In P. Hinds and S. Kiesler, editors, Distributed Work, pages 137--162. MIT Press, Cambridge, MA, 2002.Google ScholarGoogle ScholarCross RefCross Ref
  24. K. R. Lakhani and E. von Hippel. How open source software works: "free" user-to-user assistance. Research Policy, 32(6):923 -- 943, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  25. C. Lampe and E. Johnston. Follow the (slash) dot: effects of feedback on new members in an online community. In GROUP '05: Proc. of the int'l ACM conf. on supporting group work, pages 11--20, New York, NY, USA, 2005. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. C. F. Manski. Identification of Endogenous Social Effects: The Reflection Problem. Review of Economic Studies, 60:531--542, 1993.Google ScholarGoogle ScholarCross RefCross Ref
  27. D. R. Millen, J. Feinberg, and B. Kerr. Dogear: Social bookmarking in the enterprise. In CHI '06: Proc. of the ACM conf. on Human Factors in computing systems, pages 111--120, New York, NY, 2006. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. J. S. Milton and J. C. Arnold. Introduction to Probability Theory and Statistics. McGraw Hill, 2003.Google ScholarGoogle Scholar
  29. P. Resnick, K. Kuwabara, R. Zeckhauser, and E. Friedman. Reputation systems. Commun. ACM, 43(12):45--48, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. H. A. Simon. Designing organizations for an information-rich world. In M. Greenberger, editor, Computers, communications, and the public interest, pages 37--72. Johns Hopkins Press, 1971.Google ScholarGoogle Scholar
  31. C. Steglich and T. A. Snijders. Dynamic networks and behavior: Separating selection from influence. Technical report, Interuniversity Center for Social Science Theory and Methodology, University of Groningen, 2007.Google ScholarGoogle Scholar
  32. Y. Wang and D. R. Fesenmaier. Assessing Motivation of Contribution in Online Communities: An Empirical Investigation of an Online Travel Community. Electronic Markets, 13:33--45, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  33. W. W. S. Wei. Time Series Analysis, Univariate and Multivariate Methods. Pearson Addison Wesley, 2006.Google ScholarGoogle Scholar
  34. D. M. Wilkinson. Strong regularities in online peer production. In EC'08: Proc. of the 9th ACM conf. on Electronic commerce, pages 302--309, New York, NY, USA, 2008. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. F. Wu and B. A. Huberman. How public opinion forms. In Proc. WINE, volume 5385 of Lecture Notes in Computer Science, pages 334--341. Springer, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. S. Yardi, S. Golder, and M. Brzozowski. The pulse of the corporate blogosphere. In Conf. Supplement of CSCW 2008. ACM, November 8-12 2008.Google ScholarGoogle Scholar
  37. S. Yardi, S. A. Golder, and M. J. Brzozowski. Blogging at work and the corporate attention economy. In Proc. CHI 2009. ACM, to appear April 4-9 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Effects of feedback and peer pressure on contributions to enterprise social media

      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
      • Published in

        cover image ACM Conferences
        GROUP '09: Proceedings of the 2009 ACM International Conference on Supporting Group Work
        May 2009
        412 pages
        ISBN:9781605585000
        DOI:10.1145/1531674

        Copyright © 2009 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 10 May 2009

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        GROUP '09 Paper Acceptance Rate40of110submissions,36%Overall Acceptance Rate125of405submissions,31%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader