challenges in managing online business communities
DESCRIPTION
Slides from EURO 2013 conference. Overview of the ROBUST projectTRANSCRIPT
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EC Project 257859
Challenges in Managing Online Business Communities
Thomas Gottron, University Koblenz-LandauMichal Jacovi, IBMAdrian Mocan, SAP
Steffen Staab, University Koblenz-Landau
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Business Communities
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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
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Shortcomings in the Analysis
• Observation: – High activity
• Observation: – User creating many
content items
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Challenges
OnlineBusiness
CommunityModeling
AnalysisFore-casting
Data Mana-gement
Risk Mana-gement
Visuali-zation
SIOC
Behaviour
StructureContent
Metaphorbased
IndexStructures
StreamProcessing
ParallelProcessing
RiskMatrix
Simulation
RiskTracking
TreatmentPlans
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Two Examples for Metrics:Content and Structure
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Interestingness of Content
• Interestingness: intrinsic potential of content to be of interest to a wider audience
Content
I
F A
? ? ?
learn
P(A|F)
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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
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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
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Addition AUC
Removal AU
C
0.5
0.5
decay
stable growth
unstable
Quality of Indicators for Structural Dynamics
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Observations on Knowledge Networks
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Summary
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Summary
• Online Business Communities– Valuable asset– Management requires appropriate, scalable metrics
• Metrics– Content– Structure– Behaviour– Dynamics – ...
• Embedded in a larger framework for managing risks
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Thanks!
Contact:Thomas GottronWeST – Institute for Web Science and TechnologiesUniversität Koblenz-Landau [email protected]
Questions?
More Information:www.robust-project.eu
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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.