Abstract
The analysis of user behavior in online communities is a prominent topic in social media research. As such, user behavior is often analyzed using a set of metrics that describe the user’s participation behavior and structural position in the social network. Yet, for Enterprise Social Networks (ESN), i.e. internally used social networking platforms, such research is lacking. While prior studies have found users to engage in knowledge-intensive interactions, e.g. discussing and developing new ideas, little is known about how to conceptualize and measure ESN user behavior. Being able to measure user behavior, however, is an important prerequisite for the identification of knowledge management-related roles in the context of ESN.
Against this backdrop, in this chapter we derive 30 metrics that characterize the participation behavior, message content and structural position of ESN users of an Australian professional services firm. Based on a factor analysis, we identify nine distinct dimensions of ESN user behavior: Social dispersion, engagement, focus, information sharing, discussing, information seeking, response time, receiving information, and tagging. With this research we contribute to the literature by transferring concepts and methods of organization science and social media research to an ESN context. Further, our approach forms the basis for the identification of different types of knowledge actors, which might ultimately help to improve organizational knowledge transparency.
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References
Allen, J., James, A. D., & Gamlen, P. (2007). Formal versus informal knowledge networks in R&D: A case study using social network analysis. R&D Management, 37, 179–196.
Angeletou, S., Rowe, M., & Alani, H. (2011). Modelling and analysis of user behaviour in online communities. In L. Aroyo, C. Welty, H. Alani, et al. (Eds.), The semantic web—ISWC 2011 (pp. 35–50). Heidelberg: Springer.
Backhaus, K., Erichson, B., Plinke, W., & Weiber, R. (2011). Multivariate Analysemethoden: Eine anwendungsorientierte Einführung (13 ed.). Heidelberg: Springer.
Bala, H., Massey, A. P., Rajanayakam, J., & Hsieh, C. J. (2015). Challenges and outcomes of enterprise social media implementation: insights from cummins, Inc. In 2015 48th Hawaii International Conference on System Sciences (pp. 1839–1848). IEEE.
Behrendt, S., Richter, A., & Riemer, K. (2014). Conceptualisation of digital traces for the identification of informal networks in enterprise social networks. In Proceedings of the 25th Australasian Conference on Information Systems, Auckland, New Zealand.
Bernaards, C. A., & Jennrich, R. I. (2005). Gradient projection algorithms and software for arbitrary rotation criteria in factor analysis. Educational and Psychological Measurement, 65, 676–696.
Brown, J. S., & Duguid, P. (2001a). Structure and spontaneity: Knowledge and organization. In I. Nonaka & D. J. Teece (Eds.), Managing industrial knowledge: Creation transfer and utilization (pp. 44–67). London: SAGE Publications.
Brown, J. S., & Duguid, P. (2001b). Knowledge and organization: A social-practice perspective. Organization Science, 12, 198–213.
Burns, M. J., & Kotval, X. P. (2013). Questions about questions: Investigating how knowledge workers ask and answer questions. Bell Labs Technical Journal, 17, 43–61.
Chan, K., & Liebowitz, J. (2006). The synergy of social network analysis and knowledge mapping: A case study. International Journal of Management and Decision Making, 7, 19–35.
Chan, J., Hayes, C., & Daly, E. (2010). Decomposing discussion forums and boards using user roles. In W. W. Cohen & S. Gosling (Eds.), International AAAI Conference on Weblogs and Social Media 2010. (pp. 215–218). The AAAI Press.
Core Team, R. (2015). R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing http://www.r-project.org/.
Cross, R., & Prusak, L. (2002). The people who make organizations go—or stop effectiveness. Harvard Business Review, 80, 104–112.
Cross, R., Borgatti, S. P., & Parker, A. (2001a). Beyond answers: Dimensions of the advice network. Social Networks, 23, 215–235.
Cross, R., Parker, A., Prusak, L., & Borgatti, S. P. (2001b). Knowing what we know: Supporting knowledge creation and sharing in social networks. Organizational Dynamics, 30, 100–120.
Cross, R., Borgatti, S. P., & Parker, A. (2002). Making invisible work visible: Using social network analysis to support strategic collaboration. California Management Review, 44, 25–47.
Csardi, G., & Nepusz, T. (2006). The igraph software package for complex network research. International Journal of Complex Systems 1695.
Davenport, T. H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston, MA: Harvard Business School Press.
De Toni, A. F., & Nonino, F. (2010). The key roles in the informal organization: A network analysis perspective. The Learning Organization, 17, 86–103.
Eppler, M. J. (2001). Making knowledge visible through intranet knowledge maps: Concepts, elements, cases. In Proceedings of the 34th Annual Hawaii International Conference on System Sciences, Maui, HI.
Fischbach, K., Schoder, D., & Gloor, P. A. (2008). Analyse informeller Kommunikationsnetzwerke am Beispiel einer Fallstudie. Wirtschaftsinformatik, 51, 164–174.
Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks, 1, 215–239.
Friemel, T. N. (2008). Netzwerkanalytische Methoden zur Identifizierung von Kommunikationsrollen. In C. Stegbauer (Ed.), Netzwerkanalyse und Netzwerktheorie (pp. 179–190). VS Verlag für Sozialwissenschaften.
Füller, J., Hutter, K., Hautz, J., & Matzler, K. (2014). User roles and contributions in innovation-contest communities. Journal of Management Information Systems, 31, 273–308.
Gartner. (2013). Magic quadrant for social software in the workplace. https://www.jivesoftware.com/discover-jive/analyst-reports/gartner-magic-quadrant/.
Gilbert, E., & Karahalios, K. (2009). Predicting tie strength with social media. In ACM Conference on Human Factors in Computing Systems (pp. 211–220). ACM Press.
Gleave, E., Welser, H., Lento, T. M., & Smith, M. A. (2009). A Conceptual and operational definition of “Social Role” in online community. In 2009 42nd Hawaii International Conference on System Sciences (pp. 1–11). IEEE.
Grant, A. (2013). In the company of givers and takers. Harvard Business Review, 91, 90–97.
Gries, S. T. (2013). Statistics for linguistics with R: A practical introduction. Boston: De Gruyter Mouton.
Hansen, D. L., Shneiderman, B., & Smith, M. A. (2010). Visualizing threaded conversation networks: Mining message boards and email lists for actionable insights. In A. An, P. Lingras, S. Petty, & R. Huang (Eds.), Active media technology (pp. 47–62). Heidelberg: Springer.
Hansen, M. T., Nohria, N., & Tierney, T. (1999). What’s your strategy for managing knowledge? Harvard Business Review, 77, 106–116.
Helms, R., & Buijsrogge, K. (2005). Knowledge network analysis: A technique to analyze knowledge management bottlenecks in organizations. In 16th International Workshop on Database and Expert Systems Applications (DEXA’05) (pp. 410–414). Copenhagen: IEEE.
Helms, R., & Buijsrogge, K. (2006). Application of knowledge network analysis to identify knowledge sharing bottlenecks at an engineering firm. In Proceedings of the 14th European Conference on Information Systems, Göteborg, Sweden.
Hildebrandt, A., Jäckle, S., Wolf, F., & Heindl, A. (2015). Methodologie, Methoden, Forschungsdesign. Wiesbaden: Springer Fachmedien Wiesbaden. doi:10.1007/978-3-531-18993-2.
Holtzblatt, L., Drury, J., & Weiss, D. (2013). Evaluating the uses and benefits of an enterprise social media platform. Journal of Social Media and Organ, 1, 1–21.
Koch, M., Richter, A., & Schlosser, A. (2007). Produkte zum IT-gestützten social networking in unternehmen. Wirtschaftsinformatik, 49, 448–455.
Krackhardt, D., & Hanson, J. R. (1993). Informal networks: The company behind the charts. Harvard Business Review, 71, 104–111.
von Krogh, G. (2012). How does social software change knowledge management? Toward a strategic research agenda. The Journal of Strategic Information Systems, 21, 154–164.
Lehner, F. (2014). Wissensmanagement. München: Carl Hanser Verlag GmbH & Co. KG.
McAfee, A. P. (2006). Enterprise 2.0: The dawn of emergent collaboration. MIT Sloan Management Review, 47, 21–28.
McIver, D., Lengnick-Hall, C. A., Lengnick-Hall, M. L., & Ramachandran, I. (2012). Integrating knowledge and knowing: A framework for understanding knowledge-in-practice. Human Resource Management Review, 22, 86–99.
Newk-Fon Hey Tow, W., Venable, J., & Dell, P. (2012). How organisations know what they know: A survey of knowledge identification methods among Australian organisations. In Proceedings of the 23rd Australasian Conference on Information Systems, Geelong, Australia.
Parise, S., Cross, R., & Davenport, T. H. (2006). Strategies for preventing a knowledge-loss crisis. MIT Sloan Management Review, 47, 31–38.
Parise, S., Cross, R., & Davenport, T. H. (2005). It’s not what but who you know: How organizational network analysis can help address knowledge loss crises. Retrieved April 27, 2016, from http://www.robcross.org/pdf/roundtable/lost_knowledge.pdf.
Perer, A., Guy, I., Uziel, E., Ronen, I. & Jacovi, M. (2011). Visual social network analytics for relationship discovery in the enterprise. In VAST 2011—IEEE Conference on Visual Analytics Science and Technology 2011, Proceedings (pp. 71–79). IEEE.
Probst, F., Grosswiele, L., & Pfleger, R. (2013). Who will lead and who will follow: Identifikation einflussreicher Nutzer in Online Social Networks. Wirtschaftsinformatik, 55, 175–192.
Revelle, W. (2015). Psych: Procedures for psychological, psychometric, and personality research. Retrieved April 27, 2016, from http://cran.r-project.org/package=psych.
Richter, A. (2010). Der Einsatz von Social Networking Services in Unternehmen. Wiesbaden: Gabler.
Richter, A, & Riemer, K. (2009). Corporate social networking sites—modes of use and appropriation through co-evolution. In Proceedings of the 20th Australasian Conference on Information Systems, Melbourne, Australia.
Richter, A., & Riemer, K. (2013). The contextual nature of enterprise social networking: A multi case study comparison. In Proceedings of the 21st European Conference on Information Systems, Utrecht, The Netherlands.
Riemer, K., & Scifleet, P. (2012). Enterprise social networking in knowledge-intensive work practices: A case study in a professional service firm. In Proceedings of the 23rd Australasian Conference on Information Systems, Geelong, Australia.
Rowe, M., & Alani, H. (2012). What makes communities tick? Community health analysis using role compositions. In Proceedings—2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012 (pp. 267–276). IEEE.
Rowe, M., Fernandez, M., Angeletou, S., & Alani, H. (2013). Community analysis through semantic rules and role composition derivation. Web Semantics: Science, Services and Agents on the World Wide Web, 18, 31–47.
Sachs, L. (1978). Angewandte Statistik. Statistische Methoden und ihre Anwendungen. Heidelberg: Springer.
Schendera, C. F. (2010). Clusteranalyse mit SPSS. München: Oldenbourg Wissenschaftsverlag.
Schneckenberg, D. (2009). Web 2.0 and the empowerment of the knowledge worker. Journal of Knowledge Management, 13, 509–520.
Thom, J., Helsley, S., Matthews, T. L., Daly, E. M., & Millen, D. R. (2011). What are you working on? Statusmessage Q&A in an enterprise SNS. In S. Bødker, N. O. Bouvin, V. Wulf, et al. (Eds.), ECSCW2011: Proceedings of the 12th European Conference on Computer Supported Cooperative Work (pp. 313–332). London: Springer.
Trier, M., & Richter, A. (2015). The deep structure of organizational online networking—an actor-oriented case study. Information Systems Journal, 25, 465–488.
Viegas, F. B., & Smith, M. (2004). Newsgroup Crowds and AuthorLines: Visualizing the activity of individuals in conversational cyberspaces. In Proceedings of the 37th Annual Hawaii International Conference on System Sciences, Big Island, HI.
Viol, J., Bernsmann, R., & Riemer, K. (2015). Behavioural dimensions for discovering knowledge actor roles utilising enterprise social network metrics. In Proceedings of the 26th Australasian Conference on Information Systems, Adelaide, Australia.
Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.
Welser, H. T., Gleave, E., Fisher, D., & Smith, M. A. (2007). Visualizing the signatures of social roles in online discussion groups finding social roles in online discussion. Journal of Social Structure, 8, 1–32.
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Hacker, J., Bernsmann, R., Riemer, K. (2017). Dimensions of User Behavior in Enterprise Social Networks. In: Helms, R., Cranefield, J., van Reijsen, J. (eds) Social Knowledge Management in Action. Knowledge Management and Organizational Learning, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-319-45133-6_7
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