Challenges in Managing Online Business Communities


Published on

Slides from EURO 2013 conference. Overview of the ROBUST project

Published in: Science
  • Be the first to comment

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

 Challenges in Managing Online Business Communities

  1. 1. EC Project 257859 Challenges in Managing Online Business Communities Thomas Gottron, University Koblenz-Landau Michal Jacovi, IBM Adrian Mocan, SAP Steffen Staab, University Koblenz-Landau
  2. 2. Business Communities
  3. 3. Business Communities SAP Community Network (SCN)IBM Connections Communities • Customers • Partners • Suppliers • Developers Business value • Products support • Services • Find business partners Communities • Employees • Working groups • Interest Groups • Projects Business value • Task relevant information • Collaboration • Innovation Volume • 2,100,000 subscribers • 6,000 posts/day • 16GB log/day Volume • 386,000 employees • 4,000 posts/day • 1.5GB content/day Classic metrics
  4. 4. Shortcomings in the Analysis • Observation: – High activity • Observation: – User creating many content items
  5. 5. Challenges Online Business Community Modeling Analysis Fore- casting Data Mana- gement Risk Mana- gement Visuali- zation SIOC Behaviour Structure Content Metaphor based Index Structures Stream Processing Parallel Processing Risk Matrix Simulation Risk Tracking Treatment Plans
  6. 6. Two Examples for Metrics: Content and Structure
  7. 7. Interestingness of Content • Interestingness: intrinsic potential of content to be of interest to a wider audience Content I F A learn P(A|F)
  8. 8. Interestingness on Twitter My dear @johndoe had troubles to wake up this #morning Followers @janedoe RT @janedoe: My dear @johndoe had troubles to wake up this #morning F A
  9. 9. False test sets:  Afalse contains edges that do not appear  Rfalse contains edges that are not removed Network until time t1 Structural Dynamics of Networks Atrue RtrueTraining
  10. 10. Addition AUC RemovalAUC 0.5 0.5 decay stable growth unstable Quality of Indicators for Structural Dynamics
  11. 11. Observations on Knowledge Networks
  12. 12. Summary
  13. 13. Summary • Online Business Communities – Valuable asset – Management requires appropriate, scalable metrics • Metrics – Content – Structure – Behaviour – Dynamics – ... • Embedded in a larger framework for managing risks
  14. 14. Thanks! Contact: Thomas Gottron WeST – Institute for Web Science and Technologies Universität Koblenz-Landau More Information:
  15. 15. References 1. N. Naveed, T. Gottron, J. Kunegis, and A. Che Alhadi, Bad News Travel Fast: A Content- based Analysis of Interestingness on Twitter, in WebSci ’11: Proceedings of the 3rd International Conference on Web Science, 2011. 2. N. Naveed, T. Gottron, J. Kunegis, and A. Che Alhadi, Searching Microblogs: Coping with Sparsity and Document Quality, in CIKM’11: Proceedings of 20th ACM Conference on Information and Knowledge Management, pp. 183–188, 2011. 3. A. Che Alhadi, T. Gottron, J. Kunegis, and N. Naveed, LiveTweet: Microblog Retrieval Based on Interestingness, in TREC’11: Proceedings of the Text Retrieval Conference, 2011. 4. A. Che Alhadi, T. Gottron, J. Kunegis, and N. Naveed, LiveTweet: Monitoring and Predicting Interesting Microblog Posts, in ECIR’12: Procedings of the 34th European Conference on Information Retrieval, pp. 569–570, 2012. 5. T. Gottron, O. Radcke, and R. Pickhardt, On the Temporal Dynamics of Influence on the Social Semantic Web, in CSWS’12: Proceedings of the Chinese Semantic Web Symposium, 2012. 6. J. Preusse, J. Kunegis, M. Thimm, T. Gottron, and S. Staab, Structural Dynamics of Knowledge Networks, in ICWSM’13: Proceedings of the 7th International AAAI Conference on Weblogs and Social Media, 2013.