Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-10T09:03:33.875Z Has data issue: false hasContentIssue false
  • English
  • Français

Systematic community of Practice activities evaluation through Natural Language Processing: application to research projects

Published online by Cambridge University Press:  05 April 2019

Virginie Goepp ,
Nada Matta ,
Emmanuel Caillaud  and
Françoise Feugeas
Virginie Goepp*
Affiliation:
INSA de Strasbourg – Icube 24, Bld de la Victoire - 67084 Strasbourg Cedex, France
Nada Matta
Affiliation:
UTT – TechCICO12 Rue Marie Curie CS.42060 - 10004 Troyes Cedex, France
Emmanuel Caillaud
Affiliation:
Unistra, ICube 3, rue de l'université - 67084 Strasbourg Cedex, France
Françoise Feugeas
Affiliation:
INSA de Strasbourg – Icube 24, Bld de la Victoire - 67084 Strasbourg Cedex, France
*
Author for correspondence: Virginie Goepp, E-mail: virginie.goepp@insa-strasbourg.fr
Get access Rights & Permissions [Opens in a new window]

Abstract

Community of Practice (CoP) efficiency evaluation is a great deal in research. Indeed, having the possibility to know if a given CoP is successful or not is essential to better manage it over time. The existing approaches for efficiency evaluation are difficult and time-consuming to put into action on real CoPs. They require either to evaluate subjective constructs making the analysis unreliable, either to work out a knowledge interaction matrix that is difficult to set up. However, these approaches build their evaluation on the fact that a CoP is successful if knowledge is exchanged between the members. It is the case if there are some interactions between the actors involved in the CoP. Therefore, we propose to analyze these interactions through the exchanges of emails thanks to Natural Language Processing. Our approach is systematic and semi-automated. It requires the e-mails exchanged and the definition of the speech-acts that will be retrieved. We apply it on a real project-based CoP: the SEPOLBE research project that involves different expertise fields. It allows us to identify the CoP core group and to emphasize learning processes between members with different backgrounds (Microbiology, Electrochemistry and Civil engineering).

Keywords

Community of practiceNatural Language Processingperformance evaluationpragmaticsresearch project
Type
Research Article
Information
AI EDAM , Volume 33 , Special Issue 2: Knowledge Engineering and Management Applied to Innovation , May 2019 , pp. 160 - 171
Copyright
Copyright © Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Austin, JL 1975. How to do Things with Words, Vol. 367. New York: Oxford university press.Google Scholar
Baron, NS (1998) Letters by phone or speech by other means: the linguistics of email. Language & Communication 18, 133–170.Google Scholar
Borzillo, S and Kaminska-Labbe, R (2011) Unravelling the dynamics of knowledge creation in communities of practice though complexity theory lenses. Knowledge Management Research & Practice 9, 353–366.Google Scholar
Brown, JS and Duguid, P (1991) Organizational learning and communities of practice: toward a unified view of working. Organization Science 2, 40–57.Google Scholar
Carvalho, VR and Cohen, WW (2006) Improving email speech acts analysis via n-gram selection, HLT-NAACL 2006 Workshop on Analyzing Conversations in Text and Speech, Association for Computational Linguistics. Publishing, Stroudsburg, PA, USA, pp. 35–41.Google Scholar
Chu, M-T and Khosla, R (2009) Index evaluations and business strategies on communities of practice. Expert Systems with Applications 36, 1549–1558.Google Scholar
Corney, M, De Vel, O, Anderson, A and Mohay, G (2002) Gender preferential text mining of e-mail discourse, 18th Computer Security Applications Conference. Publishing, Las Vegas, NV, USA.Google Scholar
Cox, A (2005) What are communities of practice? A comparative review of four seminal works. Journal of Information Science 31, 527–540.Google Scholar
Felice, RD and Deane, P (2012) Identifying Speech Acts in Emails: Toward Automated Scoring of the TOEIC® Email Task. PublishingGoogle Scholar
Goepp, V, Munzer, C and Feugeas, F (2014) Community of Practice Theory and Process Modelling: Two Tools for Better Collaboration in Research Projects, Advances in Production management systems: Innovative and knowledge-based production management in a global-local world, APMS 2014. Publishing, Ajaccio, France.Google Scholar
Guptill, J (2005) Knowledge management in health care. Journal of Health Care Finance 31, 10–15.Google Scholar
Jeon, S-H, Kim, Y-G and Koh, J (2011) Individual, social, and organizational contexts for active knowledge sharing in communities of practice. Expert Systems with Applications 38, 12423–12431.Google Scholar
Kalia, A, Motahari Nezhad, HR, Bartolini, C and Singh, M (2013) Identifying Business Tasks and Commitments From Email and Chat Conversations. https://www.hpl.hp.com/hplabs/indexThe report reference is HPL-2013-4.Google Scholar
Kim, SJ, Hong, JY and Suh, EH (2012) A diagnosis framework for identifying the current knowledge sharing activity status in a community of practice. Expert Systems with Applications 39, 13093–13107.Google Scholar
Lampert, A, Dale, R and Paris, C (2010) Detecting emails containing requests for action, Human Language Technologies: The 11th Annual Conference of the North American Chapter of the Association for Computational Linguistics. Publishing, Los Angeles, USA, pp. 984–992.Google Scholar
Lave, J and Wenger, E (1991) Situated Learning. Legitimate Peripheral Participation. Cambridge: University Press.Google Scholar
Lee, J, Suh, E and Hong, J (2010) A maturity model based CoP evaluation framework: a case study of strategic CoPs in a Korean company. Expert Systems with Applications 37, 2670–2681.Google Scholar
Lesser, E and Everest, K (2001) Using communities of parctice to manage intellectual capital. Ivey Business Journal 65, 37–41.Google Scholar
Levinson, SC (1983) Pragmatics. Cambridge: Cambrigde University Press.Google Scholar
Matta, N, Atifi, H, Sediri, M and Sadgal, M (2011) Coordination interactions analysis in design projects. International Journal of Communication and Information Sciences, AICIT, HumanPub 1, 22–29.Google Scholar
McDermott, R (2000) Critical success factors in building communities of practice. Knowledge Management Review 3, 16–19.Google Scholar
McDermott, R (2004) How to avoid a mid-life crisis in your COPs: uncovering six keys to sustaining communities. Knowledge Management Review 42, 10–13.Google Scholar
Nonaka, I and Takeuchi, H (1995) The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New-York: Oxford University Press.Google Scholar
Probst, G and Borzillo, S (2008) Why communities of practice succeed and why they fail. European Management Journal 26, 335–347.Google Scholar
Rauscher, F, Matta, N and Atifi, F (2016) KTR: an approach that supports Knowledge extraction from design interactions, 8th IFAC Conference on Manufacturing Modelling, Management & Control (MIM). Publishing, Troyes, France.Google Scholar
Richard, JF (1990) Mental Activities, Understand, Reason, Find Solutions (in French) Les Activites Mentales, Comprendre, Raisonner, Trouver des Solutions. Paris: Armand Colin.Google Scholar
Tang, GT, Pei, J and Luk, WS (2014) Email mining: tasks, common techniques, and tools. Knowledge and Information Systems 41, 1–31.Google Scholar
Wenger, E (1998) Communities of Practice: Learning, Meaning and Identity. Cambridge: Cambridge University Press.Google Scholar
Wenger, E (2000) Communities of practice and social learning systems. Organization 7, 225–246.Google Scholar
Wenger, E and Snyder, WM (2000) Communities of practice: the organizational frontier. Harvard Business Review 78, 139–145.Google Scholar
Wenger, E, McDermott, R and Snyder, WM (2002) Cultivating Communities of Practice. Boston: Harvard Business School Press.Google Scholar
Yelati, S and Sangal, R (2011) Novel Approach for Tagging of Discourse Segments in Help-Desk E-Mails, IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). Publishing, Lyon, France, pp. 369–372.Google Scholar
Zack, MH (1999) Developing a knowledge strategy. California Management Review 41, 125–145.Google Scholar