Ralf Klamma

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What is happening in the long tail?Reliable
technologies for communities

• Ralf Klamma
• RWTH Aachen University
• FK 427 Medien und kulturelle Kommunikation
• PROLEARN Network of Excellence
• Sixth Internet Next Generation Workshop Web 2.0,
  Internet 2.0...
• Aachen, October 18, 2006

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Agenda

• Social Software Web 2.0
• Self-observation tools for Communities Social
  Software
• Collect PROLEARN Media Base
• Measure PROLEARN Measure
• Analyse PALADIN
• ATLAS Reflective Community Architecture for the
  Web 2.0
• Conclusions and Outlook

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What is Social Software?
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Social Software and Communities The Long Tail
Fragmentation
Central Core
OUT Continent
Wikipedia The Long Tail (2006)
IN Continent
Tubes
Tendrils
Islands
Albert-Laszlo Barabasi Linked The New Science
of Networks (2002)

• The Web 2.0 is a scale free, fragemented network
• Power laws (Pareto-Distribution etc.)
• 95 of users are in the Long Tail (Communities)

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Disturbances in Web 2.0

• What is happening in the long tail?
• A disturbance is an emergent phenomenon based
  on collective, distributed decisions undertaken
  by agents, having positive or negative effects on
  digital social networks.
• Disturbances occur on different levels
• Physical
• Communication
• Network
• Egocentric
• Subgroup
• Community

technical
social
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Agency in the Web 2.0 based on Patterns
Agency Empowering users to take decisions on
activity or inactivity in case of disturbances

• Abstraction Pattern as a general repeatable
  solution to a common recurring disturbance
• Basis Pattern language overcomes the
  difficulties for discovering and describing
  disturbances
• Computation Machine-readable description of the
  patterns - XML-based pattern language for
  multidimensional disturbances
• Discovery Automatic Analysis of digital social
  networks for disturbances with the pattern
  language

• Analysis of Agency Patienthood phenomena on
  the Web 2.0
• Which discourses can be expected in the (near)
  future?
• What influence do different media have on
  communities?
• What are the impacts of my actions on the
  community?
• Which event(s) should have taken place?
• How will the community/ies evolve?

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Measure, Analyse, and Simulate PROLEARN Media
Base

• Social Software data from E-learning Communities
• Mailing lists
• Newsletter
• Websites
• RSS Feeds
• Blogs
• Database support by IBM DB2, eXist, Oracle, ...
• Web Interface based on Plone/Zope
• Visualization of
• Graphs
• Tree Maps
• ...

www.prolearn-academy.org
ECTEL 2006
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Pattern by Example Troll

• Troll Pattern This pattern tries to discover the
  cases when a troll exists in a digital social
  network. A troll in the network is considered a
  disturbance.
• Disturbance
• (EXISTS medium medium.affordance
  threadArtefact)
• (EXISTS troll (EXISTS thread (thread.author
  troll)
• (COUNT message (message.author troll)
  
• (message.posted thread)) gt minPosts)
• (EXISTS thread1, message1
  (thread1.author1 ! troll)
• (message1.author troll message1.posted
  thread1 ))))
• Forces medium troll network member thread
  message url
• Force Relations neighbour(troll, member) own
  thread(troll, thread)
• Solution No attention must be paid to the
  discussions started by the troll.
• Rationale The troll needs attention to continue
  its activities. If no attention is paid, he/she
  will stop participating in the discussions.
• Pattern Relations Associates Spammer pattern.

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Spammer Visualization

• (?medium medium.affordance threadArtefact)
  ?
• (?spammer (COUNTthread (thread.author
  spammer) gt minThreadCount)) ?
• ((??thread1 (thread1.author spammer) ?
• (COUNTmessage (message.posted thread) gt
  maxMessageCount)))

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Structural Hole Visualization

• (? m (1 - (2/((COUNTnn.neighbourm)
• (COUNTp(p!n) ?
• ((p.neighbourn ) ? (p.neighbourm) ?
  (n.neighbourm)))))) gt efficiencyParameter)

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Research ApproachReflective Community Platform

Support evolving learning communities

(repeated assessment of community requirements)

Self monitoring tools

for Communities

Measure,


Social Software
Analyse,

Development
Simulate



Service-oriented Community Platform


Assessment requirements for Communities

Based on Preece 2001, cf. JUKM 2006 for details
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Conclusions

• Social Software Web 2.0
• Emergent phenomenon
• 95 of Web 2.0 are fragmented communities
• Agency and Patienthood as challenges for
  communities in the Web 2.0
• Self-observation and reflection of communities
• Collect Measure ATLAS Media Base and ATLAS
  Measure
• Analyse Pattern identification with PALADIN

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Promotion

• Professional Training Facts
• www.prolearn.eu
• IAO, Stuttgart, November 14-15, 2006
• Social Software Web 2.0 Workshop
• Track Future of E-Learning with Siemens,
  Deutsche Telekom ...
• Symposium in Media Informatics
• www.medien-informatik.eu
• B-IT, Bonn, November 16-17 2006
• Contributions by Microsoft, SAP, Deutsche
  Telekom, Buhl Data ...
• Workshops about Web 2.0, Social Software, TEL and
  Media Conflicts