Community Analytics – An Information Systems Perspective Ralf Klamma CRIWG 2012 Raesfeld, Germany, September 17, 2012

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