challenges in managing online business communities

EC Project 257859

 Challenges in Managing Online Business Communities

Thomas Gottron, University Koblenz-LandauMichal Jacovi, IBMAdrian Mocan, SAP

Steffen Staab, University Koblenz-Landau

Business Communities

Business Communities

SAP Community Network (SCN)IBM ConnectionsCommunities• 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

Shortcomings in the Analysis

• Observation: – High activity

• Observation: – User creating many

content items

Challenges

OnlineBusiness

CommunityModeling

AnalysisFore-casting

Data Mana-gement

Risk Mana-gement

Visuali-zation

SIOC

Behaviour

StructureContent

Metaphorbased

IndexStructures

StreamProcessing

ParallelProcessing

RiskMatrix

Simulation

RiskTracking

TreatmentPlans

Two Examples for Metrics:Content and Structure

Interestingness of Content

• Interestingness: intrinsic potential of content to be of interest to a wider audience

Content

I

F A

? ? ?

learn

P(A|F)

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

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

Addition AUC

Removal AU

C

0.5

0.5

decay

stable growth

unstable

Quality of Indicators for Structural Dynamics

Observations on Knowledge Networks

Summary

Summary

• Online Business Communities– Valuable asset– Management requires appropriate, scalable metrics

• Metrics– Content– Structure– Behaviour– Dynamics – ...

• Embedded in a larger framework for managing risks

Thanks!

Contact:Thomas GottronWeST – Institute for Web Science and TechnologiesUniversität Koblenz-Landau gottron@uni-koblenz.de

Questions?

More Information:www.robust-project.eu

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.