Community Analytics – An Information Systems Perspective
2 likes2,747 views
The document discusses the role of community analytics in supporting professional communities and enhancing their interactions through advanced community information systems. It emphasizes the need for a combination of quantitative and qualitative analytics to understand community goals, processes, and member interactions, alongside presenting various case studies and methodologies. Additionally, it highlights the ongoing development of community analytics as essential in leveraging big data and maintaining engagement within these communities.
Community Analytics – An Information Systems Perspective
- 1. TeLLNet Community Analytics – y y An Information Systems Perspective Ralf Klamma & ACIS Groupp RWTH Aachen University Advanced Community Information Systems (ACIS) klamma@dbis.rwth-aachen.de Lehrstuhl Informatik 5 CRIWG 2012 R f ld G 2012, Raesfeld, Germany, S t b 17, 2012 September 17 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-1 This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.
- 2. Advanced Community Information Systems (ACIS) TeLLNet ering Responsive Community We Analytics Open Visualization Community eb andd nginee Information Simulation Systems Web En Community Community Support Analytics W Lehrstuhl Informatik 5 Requirements R i t (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-2 Engineering
- 3. Agenda TeLLNet nformation Systems Conclusions & Outllook tics Commu Analyt Use Cases unity mmunity In Com Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-3
- 4. Abstract Information Systems serve the needs of organizations. With the y g TeLLNet widespread availability of free Web-based tools and social networking sites also communities with no institutional backing intensify the use of the W b In this th Web. I thi presentation, I motivate b examples th t t ti ti t by l that professional communities need community support beyond the commodity level Community analytics in such settings need a deep level. understanding of interactions between community members and systems, members and resources as well as members among each y g others. Such a perspective is delivered by community information systems serving the needs of professional communities. The meaningfull combination of quantitative and qualitative analytics i f bi ti f tit ti d lit ti l ti strategies supports the understanding of community goals, community processes and community reflection Case studies from ongoing EU reflection. Lehrstuhl Informatik 5 (Information Systems) research projects will support the argumentation. Prof. Dr. M. Jarke I5-Klamma-0912-4
- 5. TeLLNet COMMUNITY INFORMATION SYSTEMS Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-5
- 6. A Brief History of Community Information Systems Organisational Memories M i TeLLNet (XML, HTML, Communities of XTM) (Web 2.0) Practice Business Processes Social Software Semantic (XML, HTTP, Web RSS) (XML, RDF, Meta Ontologien) Groupware / Data Workflows E-Learning EL i Media (XML, (XML (XML, LOM, Traces BPEL) XML-RPC) Multimedia Web Services (XML, VRML, (XML, WSDL, Digital Media SOAP,UDDI) DC, MPEG) Technology Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke Klamma: Social Software and Community Information Systems, 2010 I5-Klamma-0912-6
- 7. Communities of Practice Communities of practice ( p (CoP) are groups of p p ) g p people TeLLNet who share a concern or a passion for something they do and who interact regularly to learn how to do it g y better (Wenger, 1998) Community Analytics Support – How can CoPs record their complex complex media traces and how they can deal with them? – Can CoPs continuously elicitate and implement requirements? How much computer science support is needed? – C C P llearn meaningfull di it l sociall I t Can CoPs i f digital i Interaction and make use ti d k of disturbances? – Can CoPs maintain or even improve their agency (Learning (Learning, Lehrstuhl Informatik 5 (Information Systems) Researching, Working) in the Web 2.0? Prof. Dr. M. Jarke I5-Klamma-0912-7
- 8. TeLLNet COMMUNITY ANALYTICS Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-8
- 9. Proposed Professional Development of the Community Analytics Field Will happen Big Data by Digital Eco Systems ( pp g y g y (Quantitative Analysis) y ) TeLLNet – A plethora of targets (Small Birds) – Professional Communities are distributed in a long tail – Professional Communities use a digital eco system – An arsenal of weapons (Big Guns) – A growing number of community analytics methods – Combined methods from machine intelligence and knowledge representation May t happen D M not h Deep I l Involvment with community t ith it (Qualitative Analysis) – Domain knowledge for sense making – Passion for community and sense of belonging – Community learns as a whole → Community Analytics for the Community by the Community Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-9
- 10. Interdisciplinary Multidimensional Model of Communities Collection of CoP Digital Traces in a MediaBase TeLLNet – Post-Mortem Crawlers – Real-time, mobile, protocol-based (MobSOS) – (Automatic) metadata generation by Social Network Analysis Social Requirements Engineering with i* Framework for defining goals and dependencies in CoP Social Software Media Networks Network of Artifacts Cross-Media Social Network Content Analysis on Microcontent, Blog entry, Message, Analysis on Wiki Blog Podcast Wiki, Blog, Podcast, Burst, Th d C B t Thread, Comment, Conversation, Feedback (Rating) t C ti F db k (R ti ) IM, Chat, Email, Newsgroup, Chat … Web 2.0 Business Processes (i*) (Structural, Cross-media) Network of Members Lehrstuhl Informatik 5 Members (Information Systems) (Social Network Analysis: Centrality, Efficiency, Community Detection) Prof. Dr. M. Jarke Communities of practice I5-Klamma-0912-10
- 11. MediaBase: Cross Media / Cross Community SNA Post-Mortem Collection of Attribute has Actor TeLLNet Social Software artifacts with isA parameterized PERL scripts – Blogs & Wikis – Mails & Forums Medium (Social Software) Artifact Member Community – Web pages Database support by IBM DB2, eXist, Oracle, ... Web Interface based on Firefox Plugin, Plone, Drupal, LAS, ... – www.learningfrontiers.eu g – www.prolearn-academy.org Strategies of visualization – Widget-based charts Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke – Cross-media graphs I5-Klamma-0912-11 Klamma et al.: Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe, EC-TEL 2006
- 12. Models of Community Success from an Information Systems Perspective TeLLNet Reference Model: D&M IS Success Model (1992) – Based on >100 Empirical/Conceptual Studies p p – Validated by Independent Studies Updated MobSOS Model: Integration of Future Web Concepts – Mobility – Real-Time Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke – Protocol-based (HTTP, XMPP, RESTful) I5-Klamma-0912-12
- 13. MobSOS Survey Module Testbed: MobSOS Survey TeLLNet Service – Survey Management – Survey Participation – XML/Relational DB Schema – Questionnaire XML Schema – Adaptive Templates Client: MobSOS Surveys – S Survey P ti i ti Participation – Mobile Application Lehrstuhl Informatik 5 – W bb d Web-based (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-13
- 14. MobSOS Success Model Overview TeLLNet Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-14
- 15. MobSOS Test beds Analytics & Visualization beds, TeLLNet Context-Aware Usage/Error Statistics S i l N t k Analysis Social Network A l i Service Quality Analysis Visualization Set of MobSOS Widgets & Services interactive data mining visualization Lehrstuhl Informatik 5 Dominik Renzel, Ralf Klamma (Information Systems) Semantic Monitoring and Analyzing Context-aware Collaborative Multimedia Services Prof. Dr. M. Jarke I5-Klamma-0912-15 2009 IEEE International Conference on Semantic Computing, 14-16 September 2009 / Berkeley, CA, USA
- 16. Community Analytics in CoP User-to-Service Communication TeLLNet • CoP-aware Usage Statistics • Identification of successful CoP services • Identification of CoP service usage patterns User to User User-to-User Communication • CoP-aware Social Network Analysis • Identification of influential CoP members • Identification of CoP member interaction/learning patterns Lehrstuhl Informatik 5 (Information Systems) + Prof. Dr. M. Jarke I5-Klamma-0912-16
- 17. Supporting Community Practice with the MobSOS Success Model TeLLNet Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-17
- 18. Community SRE Processes– i* Strategic Rationale TeLLNet Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-18
- 19. ROLE Requirements Bazaar – Community-aware R C it Requirements P i iti ti i t Prioritization TeLLNet Community-dependent C it d d t requirements ranking lists Factors influencing requirements ranking User-controlled weighting of ranking factors Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-19
- 20. TeLLNet ROLE & TELMAP CASE STUDIES Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-20
- 21. Research Context: Responsive Open Learning Environments (ROLE) TeLLNet Focus of key research objectives: • Empower the learner to build their ROLE Vi i Vision own responsive learning environment • Awareness and reflection of own Responsiveness l i learning process • Individually adapted composition of User-Centered personal learning environment Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-21
- 22. Self-Regulated Self Regulated Learning TeLLNet learner input regarding goals, preferences, … learner profile information is defined and revised evaluation and creating PLE self-evaluation plan learner reflects and reacts learner finds and selects on strategies, achievements, g , , learning resources and usefulness reflect learn recommendations feedback from peers or tutors (from different sources) learner works on selected learning resources l i assessment and attaining skills using different self-assessment learning events (8LEM) recommen-dations be aware of monitoring it i learner should understand and ROLE infrastructure should control own learning process provide adaptive guidance Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-22
- 23. Preparation for English Language Tests Urch Forums (formerly TestMagic) User of clique TeLLNet Non-clique – Community on preparation for English User in thread language tests Clique-user Thread 1 Thread 2 missing in – 120,000+ threads, 800,000 pos s, 0,000 eads, 800,000+ posts, thread th d 100,000+ users over 10 years – Social Network Analysis, Machine Thread 3 Learning and Natural Language Processing What are the goals of learners? – Intent Analysis (Phases 1 & 2) Time What are their expressions? – Sentiment Analysis (Phases 3 & 4) Refinement – 12881 cliques with avg. size 5 and avg. occurrence of 14 Lehrstuhl Informatik 5 Petrushyna, Kravcik, Klamma: (Information Systems) Learning Analytics for Communities of Lifelong Learners: a Forum Case. Prof. Dr. M. Jarke I5-Klamma-0912-26 ICALT 2011
- 24. Self-Regulated Learning Phases Can Be Observed in Communities Different users Phase 1 and 2 (low sentiment, questioner, lot of intents) TeLLNet Phase 3 (increasing sentiment, conversationalist) Phase 4 (high sentiment, answering person) 1 week / step Lehrstuhl Informatik 5 (Information Systems) 40% of „footprints“ of cliques align with model for phases Prof. Dr. M. Jarke I5-Klamma-0912-27
- 25. Research Context: Roadmapping Technology Enhanced Learning TeLLNet Mapping and roadmapping for TEL Understanding the current TEL landscape g p Strong and weak signals for change at different levels Different data sources Different methods, e.g. Delphi, Community modeling, Text analysis Social Network Analysis, etc. analysis, Analysis etc Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-28
- 26. TEL Projects TeLLNet Project as a funded collaborative R&D effort Important role in the R&D value chain Points of interest: – Organizational collaboration – Progression of consortia – Impact on the landscape Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-29
- 27. Data Set Progr. Call # Projects (acronyms) Call 2005 4 CITER, JEM, MACE, MELT TeLLNet Call 2006 7 COSMOS, EdReNe, EUROGENE, eVip, Intergeo, KeyToNature, Organic.Edunet ECP Call 2007 3 ASPECT, iCOPER, EduTubePlus Call 2008 5 LiLa, Math-Bridge, mEducator, OpenScienceResources, OpenScout IST-2002- CONNECT, E-LEGI, ICLASS, KALEIDOSCOPE, LEACTIVEMATH, PROLEARN, 8 2.3.1.12a TELCERT, UNFOLD , IST-2004- APOSDLE, ARGUNAUT, ATGENTIVE, COOPER, ECIRCUS, ELEKTRA, I-MAESTRO, FP6 2.4.10b 14 KP-LAB, L2C, LEAD, PALETTE, PROLIX, RE.MATH, TENCOMPETENCE IST-2004- ARISE, CALIBRATE ELU EMAPPS COM ICAMP LOGOS LT4EL MGBL UNITE ARISE CALIBRATE, ELU, EMAPPS.COM, ICAMP, LOGOS, LT4EL, MGBL, UNITE, 10 2.4.13c VEMUS ICT-2007.4.1d 6 80DAYS, GRAPPLE, IDSPACE, LTFLL, MATURE, SCY ICT-2007.4.3d 7 COSPATIAL, DYNALEARN, INTELLEO, ROLE, STELLAR, TARGET, XDELIA FP7 ALICE, ARISTOTELE, ECUTE, GALA, IMREAL, ITEC, METAFORA, MIROR, ICT-2009.4.2b 13 MIRROR, NEXT-TELL, SIREN, TEL-MAP, TERENCE Lehrstuhl Informatik 5 Total: 77 (Information Systems) a … Technology-enhanced learning and access to cultural heritage” c … Strengthening the Integration of the ICT research effort in an Enlarged Europe” Prof. Dr. M. Jarke I5-Klamma-0912-30 b … Technology-Enhanced Learning d … Digital libraries and technology-enhanced learning”
- 28. TEL Projects as Social Networks Projects x Organizations j g TeLLNet Project consortium progression – Nodes: Projects IMC, RWTH, ROLE OU, OU ZSI – Ed Edges: O l of consortia Overlap f ti (directed, weighted) TEL-Map Organizational collaboration – N d O Nodes: Organiziations i i i The Open STELLAR, EUROGENE, University ROLE, PROLEARN, – Edges: Collaboration in iCOPER, ASPECT multiple projects lti l j t KU Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke (undirected, weighted) Leuven I5-Klamma-0912-31
- 29. Consortium Progression Network At least 2 overlapping partners TeLLNet At least 3 months time between project start d t l t th ti b t j t t t dates 68 projects, 198 connections Node size proportional to weighted degree p p g g Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-32
- 30. Project Impact on the Landscape TeLLNet Successor projects relative to opportunity Cumulative fraction of successor Lehrstuhl Informatik 5 projects filled up with p's members (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-33 Derntl, Klamma: European TEL Projects Community. EC-TEL 2012.
- 31. Impact Graph All programmes p g t = 3 months TeLLNet k=2 represented, with FP6 strongest Node size proportional to impact Best impact for money: PROLEARN, ICOPER, GRAPPLE All past networks of excellence among top five ranks. p Lehrstuhl Informatik 5 Several running or recently The two inaugural (Information Systems) Prof. Dr. M. Jarke completed projects NoEs on top I5-Klamma-0912-34
- 32. Expected Impact? Correlation between weighted in-degree and impact TeLLNet iin progression graph i h Stronger incoming connections appears to lead to higher impact 50 45 ICOPER STELLAR 40 Weighted In-Degree 35 30 GRAPPLE 25 20 ASPECT 15 LTFLL 10 MACE 5 Filter: Project start > 2005 0 Lehrstuhl Informatik 5 (Information Systems) 0 0.1 0.2 0.3 0.4 Prof. Dr. M. Jarke Impact I5-Klamma-0912-35
- 33. Future Gazing TeLLNet GALA 53 50 OpenScout 45 ICOPER 46 STELLAR 40 ROLE Weighted In-Degree e 35 32 30 29 GRAPPLE 25 iTEC TEL-MAP TEL MAP d 20 20 ASPECT 15 LTFLL 10 MACE 5 0 Lehrstuhl Informatik 5 0 0.1 0.2 0.3 0.4 (Information Systems) Prof. Dr. M. Jarke Impact I5-Klamma-0912-36
- 34. In-Degree In Degree – “Expected Impact” TeLLNet Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-37
- 35. Most Frequent Collaborators TeLLNet 1. PROLEARN (FP6): 16 pairs 4. GRAPPLE (FP7): 8 pairs, 2. 2 ICOPER (ECP): 10 pairs 5. 5 STELLAR (FP7) ROLE (FP7) (FP7), (FP7), Lehrstuhl Informatik 5 (Information Systems) 3. OpenScout (ECP): 9 pairs PROLIX (FP6): 5 pairs Prof. Dr. M. Jarke I5-Klamma-0912-38
- 36. Projects Space @ LearningFrontiers.eu LearningFrontiers eu TeLLNet Lehrstuhl Informatik 5 (Information Systems) Prof. Dr. M. Jarke I5-Klamma-0912-39
- 37. TEL Mediabase Dashboard http://learningfrontiers.eu/?q=dashboard TeLLNet Derntl, Erdtmann, Klamma: An Lehrstuhl Informatik 5 (Information Systems) embeddable widget-based dashboard Prof. Dr. M. Jarke for visual analytics on scientific I5-Klamma-0912-40 communities. I-KNOW 2012
- 38. Advanced Community Information Systems • LAS & Services • SNA TeLLNet • ROLE Sandbox • Widgets Responsive • Network • Advanced Community y Models Open Web & Visualization Community • Network Multimedia & Simulation Environments Analysis ring Technologies • Actor Network Web Analytics • XMPP Theory Web Engineer • HTML5 • Communities of • MPEG-7 Community Community Practice • Web Support Analytics • Game Theory Services • Community Detection A • RESTf l RESTful • Requirements • MediaBase Bazaar • MobSOS • Web Mining • LAS • Recommender • Cloud Systems Computing • Multi Agent • Mobile Simulation Sim lation Computing Social Requirements Engineering • Agent and Goal Oriented i* Modeling Lehrstuhl Informatik 5 (Information Systems) • Participatory Community Design Prof. Dr. M. Jarke I5-Klamma-0912-41