Reflection Support for Communities on the Web


Published on

Multi-Actor Systems Research Seminar
TU Delft
February 19, 2010

Published in: Technology, Business
1 Like
  • Be the first to comment

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

No notes for slide

Reflection Support for Communities on the Web

  1. 1. TeLLNet Reflection Support for Communities on the Web Ralf Klamma RWTH Aachen University TU Delft, February 19, 2010 Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-1
  2. 2. I5-RK-0210-2 Prof. Dr. M. Jarke TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) RWTH Aachen Community Information Systems Data Management: Mediabases PALADIN Case Studies Agenda Conclusions and Outlook
  3. 3. RWTH Aachen University • 260 institutes in 9 faculties as Europe’s leading institutions for science and research TeLLNet • Currently around 31,400 students are enrolled in over 100 academic programs • Over 5,000 of them are international students hailing from 120 different countries • 1,250 spin-off businesses have created around 30,000 jobs in the greater Aachen region over the past 20 years. • IDEA League • Germany’s Excellence Initiative: 3 clusters of excellence, a graduate school Lehrstuhl Informatik 5 and the institutional strategy “RWTH Aachen 2020: Meeting Global Challenges” (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-3
  4. 4. Community Information Systems Research Group TeLLNet  Established at DBIS chair, RWTH Aachen University  9 Phd students & researchers  10-15 paid student workers & thesis workers Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-4
  5. 5. Communities of Practice TeLLNet Analysis of Traces of CoPs in the Web Community of practice (CoP) as the Engineering of basic research object Community for our Web Science Information Systems approach Communities of practice are groups of people who share a concern or a passion for something they do and who interact regularly to learn how Wenger: Communities of Practice: Lehrstuhl Informatik 5 (Informationssysteme) to do it better Learning, Meaning and Prof. Dr. M. Jarke Identity, 1998 I5-RK-0210-5
  6. 6. i* Model of Requirements Engineering in CoP TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-6
  7. 7. ATLAS: Reflective IS as an Architectural Foundation Operational Support Community Reflective Support Self-Modeling TeLLNet Can we support CoPs with the Can CoPs continuously elicit and collaborative creation of complex implement requirements? How much multimedia objects? computer science support is needed? Community Can CoPs make use of metadata over Can CoPs learn meaningful social the frontiers of media and standards? Self-Observation interaction and make use of disturbances? Can we support CoPs by personalized How can CoPs record their complex knowledge management and networking media learning traces and how they can strategies in Social Software? deal with them? How do adaptive, mobile web-based Can CoPs maintain or even improve their interfaces for CoPs look like? agency (Learning, Researching, Working) in the Web 2.0? Actor- Agent-oriented Network RE Community Theory Information Systems Social Participatory Community Game Network Design IS Design Theory Analysis Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-7 Communities of Practice Media Networks
  8. 8. Solution idea for Reflective Support: Cross-Media Social Network Analysis  Interdisciplinary multidimensional model of digital networks TeLLNet – Social network analysis (SNA) is defining measures for social relations – Actor network theory (ANT) is connecting human and media agents – I* framework is defining strategic goals and dependencies – Theory of media transcriptions is studying cross-media knowledge social software Media Networks network of artifacts Wiki, Blog, Podcast, IM, Chat, Microcontent, Blog entry, Message, Burst, Thread, Email, Newsgroup, Chat … Comment, Conversation, Feedback (Rating) i*-Dependencies (Structural, Cross-media) network of members Lehrstuhl Informatik 5 Members (Social Network Analysis: Centrality, (Informationssysteme) Prof. Dr. M. Jarke Efficiency) Communities of practice I5-RK-0210-8
  9. 9. Simplified Meta Model Attribute has Actor TeLLNet isA Medium Artifact Process Member Community isA stores creates is affected by belongs go represents consumes performs ranks Lehrstuhl Informatik 5 Browse Address Transcribe … Localize (Informationssysteme) Prof. Dr. M. Jarke Latour: On Recalling ANT, 1999 I5-RK-0210-9
  10. 10. MediaBase  Collection of Social Software artifacts with parameterized TeLLNet PERL scripts – Mailing lists – Newsletter – Web sites – RSS Feeds – Blogs  Database support by IBM DB2, eXist, Oracle, ...  Web Interface based on Firefox Plugin, Plone/Zope, LAS, ...  Strategies of visualization – Tree maps Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke – Cross-media graphs I5-RK-0210-10 Klamma et al.: Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe, EC-TEL 2006
  11. 11. Media Base Web 2.0 Commander  Personalization (user annotates resources with tags and has his page) TeLLNet  Community-awareness (resources and annotation of others are open)  User-friendly interface (Firefox plug-in, easy insertion of resources, tags, tracking of recent changes) Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-11
  12. 12. Modeling Dependencies Using the i* Framework Coordination Iterant Coordinator Broker TeLLNet isA isA isA Member Gatekeeper Artifact isA URL Hub Legend: Agent Goal Communication Network Resource Lehrstuhl Informatik 5 Task (Informationssysteme) Prof. Dr. M. Jarke Eric S. K. Yu, Towards Modeling and Reasoning Support for Early-Phase Requirements Engineering, RE 1997 I5-RK-0210-12
  13. 13. Web 2.0 Media Operations in ATLAS TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-13
  14. 14. PALADIN: Disturbances in Cross-media Social Networks  What is a disturbance? TeLLNet – Sensing an incompatibility between theories exposed and theories-in-use  Disturbances are starting points of learning processes – Disturbances disturb, prevent … but they are creating reflection  Disturbances are hard to detect or to forecast Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-14
  15. 15. Pattern Language for PALADIN: 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. TeLLNet Disturbance: (EXISTS [medium | medium.affordance = threadArtefact]) & (EXISTS [troll |(EXISTS [thread | ( = troll) & (COUNT [message | ( = troll) & (message.posted = thread)]) > minPosts]) & (~EXISTS[ thread1, message1| (thread1.author1 != troll) & ( = 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 Lehrstuhl Informatik 5 will stop participating in the discussions. Pattern Relations: Associates Spammer pattern. (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-15
  16. 16. Pattern Discovery Process Pattern 1. Set pattern Pattern Template parameters Disturbance Disturbance TeLLNet Variables Pattern 4a. Variables Parameters Change Pattern Instance Pattern Parameters Disturbance Digital Social Network 2. Instantiate disturbances 4b. Apply Variables Pattern Pattern Solution Parameters Pattern Template Instance Forces Force Relations Disturbance Instances Description Solution Variables Pattern Parameters Rationale Dependencies 3. Evaluate disturbances Lehrstuhl Informatik 5 (Informationssysteme) Pattern Relations Prof. Dr. M. Jarke I5-RK-0210-16
  17. 17. PALADIN Case Study 10 patterns of disturbance over 119 social network instances, TeLLNet 17359 individuals, 215 345 mails Pattern Occurrences Remarks Burst 22 The pattern finds out topics which were very important for certain period of time. Scalability is necessary. No Conversationalist 76 The existence implies little communication in the network. No Questioner 67 The existence implies that the network is not popular. No Answering Person 61 Occurs in small networks. The effects of the lack of an answering person must be further checked with content analysis. Troll 2 Troll occurs very rarely in cultural communities. True negatives exist. Spammer 86 Spammers can be found often in discussion groups. False positives exist. Leader 37 The pattern occurs in the network centered around a member. No Leader 40 Occurs in big networks where the members are distributed in different clusters. Structural Hole 67 Occurs for members having neighbors with only one contact. Lehrstuhl Informatik 5 (Informationssysteme) Independent 13 Occurs in large networks where disconnected subnetworks exist. Prof. Dr. M. Jarke I5-RK-0210-17 Discussions Scalability is necessary.
  18. 18. Social Network Analysis of Open Source Communities  Eclipse components network based on analysis of TeLLNet source code repository (Software Architecture)  Eclipse components network based on analysis of mailing list communication (Social Structure) Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-18
  19. 19. Community Reflection about Development Process TeLLNet  Social platform: Eclipse forum eclipsezone  Forum: Eclipse communication framework (ECF)  Measure: degree centrality Lehrstuhl Informatik 5 (Informationssysteme)  Statistics: 225 nodes, 283 edges Prof. Dr. M. Jarke I5-RK-0210-19
  20. 20. Conversationalist Pattern  Social platform: Eclipse mailing list TeLLNet  Forum: Device debugging developer discussion Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-20
  21. 21. Questioner Pattern  Social platform: Eclipse mailing list TeLLNet  Forum: Device debugging developer discussion Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-21
  22. 22. Correlation Estimation between Architecture and Social Structure TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-22
  23. 23. Requirements Reflection Compared to Community Performance  With increasing number of boundary spanners it becomes TeLLNet easier to induce / implement requirements, which can be evidenced by increased release rates and vice-versa  As most bugs are due to insufficient understanding [NOHI99] and knowledge creation as well as sharing is supported by boundary spanners [BDBu07], then increased number of boundary spanners should be evidenced by decreased bug rate and vice-versa Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-23
  24. 24. Identification of End-Users and Developers in OSS Communities Community TeLLNet Clustering Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-24
  25. 25. Textual Analysis of Postings from Community Experts TeLLNet Postings from experts of one of the identified communities Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-25
  26. 26. Knowledge Network of Computer Science with AERCS  Knowledge network to understand major research areas and how they TeLLNet are interconnected  Dataset: combination of DBLP and CiteSeerX - DBLP: 788,259 author’s names, 1,226,412 publications, 3,490 series. - CiteSeerX: 7,385,652 publications; 22,735,140 references and over 4 million author’s names - Matching: 70% publications in DBLP using canopy clustering technique  Method: - Citation analysis: bibliographic coupling - Relatedness measure: cosine similarity - Series cluster analysis  Visualization: Lehrstuhl Informatik 5 - yFiles organic layout (forced-directed paradigm) (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-26
  27. 27. Knowledge Network: the Visualization TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-27
  28. 28. Interdisciplinary Series: Top Betweenness Centrality TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-28
  29. 29. High Prestige Series: Top PageRank TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-29
  30. 30. TeLLNet: SNA for European Teachers‘ Life Long Learning TeLLNet Management Analysis Visualization  How to manage and handle large scale data on social networks?  How to analyse social network data in order to develop teachers’ competence, e.g. to facilitate a better project collaboration?  How to make the network visualization useful for teachers’ lifelong learning? Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-30
  31. 31. eTwinning Network Information Visualization TeLLNet • Teacher network 2008 as example Lehrstuhl Informatik 5 •Cooperation among countries (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-31
  32. 32. Visual Analytics • Labels and dates help to identify complete substructures TeLLNet • substructures Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-32
  33. 33. Meta Competence Development for TeLLNet TeLLNet Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-33
  34. 34. Network Simulation & Evaluation  Network Simulation  Teachers profiles (skills, knowledge, identity) TeLLNet  Identification of payoffs and strategies  Network formation  Network Evaluation  Nash equilibrium (win-win situation)  Quality labels Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-34
  35. 35. Conclusions  Can CoPs continuously elicit and implement requirements? – Eclipse case study TeLLNet – EU IP ROLE: RE for personal learning environments  Can CoPs learn meaningful social interaction and make use of disturbances? – Pattern-based Cross-Media Network Analysis – PALADIN case study  How can CoPs record their complex media learning traces and how they can deal with them? – Media Bases – AERCS case study  Can CoPs maintain or even improve their agency (Learning, Researching, Working) in the Web 2.0? – Measurement, Analysis and Simulation – TellNet case study Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke I5-RK-0210-35
  36. 36. Outlook  Cloud Data Management for Communities TeLLNet – Data uncertainty & security management – Scaling up analysis in cloud computing  Mobile Social Software – Merging Virtual Campfire and spatiotemporal social network analysis  Self-Modeling and Self-Observation of Communities – End-user developement for social network analysis – Development of meta-competences Lehrstuhl Informatik 5 (Informationssysteme) Prof. Dr. M. Jarke – Lesser need for computer science & IT experts I5-RK-0210-36