Slides from EURO 2013 conference. Overview of the ROBUST project

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. Business Communities

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. Shortcomings in the Analysis
• Observation:
– High activity
• Observation:
– User creating many
content items

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. Two Examples for Metrics:
Content and Structure

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. 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. 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. Addition AUC
RemovalAUC
0.5
0.5
decay
stable growth
unstable
Quality of Indicators for Structural Dynamics

11. Observations on Knowledge Networks

12. Summary

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. Thanks!
Contact:
Thomas Gottron
WeST – Institute for Web Science and Technologies
Universität Koblenz-Landau
gottron@uni-koblenz.de
More Information:
www.robust-project.eu

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.