Reflection Support for Communities on the Web

Lehrstuhl Informatik 5(Informationssysteme)

Prof. Dr. M. JarkeI5-RK-0210-1

TeLLNet

Ralf KlammaRWTH Aachen UniversityTU Delft, February 19, 2010

Reflection Support for Communities on the Web



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Agenda

RWTH

Aac

hen

Comm

unity

Infor

matio

n Sy

stems

Data

Mana

geme

nt: M

ediab

ases

PALA

DIN

Case

Stud

ies

Conc

lusion

s and

Outl

ook



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RWTH Aachen University

• 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 and the institutional strategy “RWTH Aachen 2020: Meeting Global Challenges”

• 260 institutes in 9 faculties as Europe’s leading institutions for science and research

• 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



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Community Information Systems Research Group

Established at DBIS chair, RWTH Aachen University 9 Phd students & researchers 10-15 paid student workers & thesis workers



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Communities of Practice

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

to do it better

Community of practice (CoP) as the basic research object for our Web Science

approach

Analysis of Traces of CoPs in the Web

Engineering of Community

Information Systems

Wenger: Communities of Practice: Learning, Meaning and Identity, 1998



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i* Model of Requirements Engineering in CoP



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ATLAS: Reflective IS as an Architectural Foundation

Communities of Practice Media Networks

Community Information Systems

Agent-oriented RE

Community IS Design

Participatory Design

CommunitySelf-Observation

CommunitySelf-Modeling

Operational SupportCan we support CoPs with the collaborative creation of complex multimedia objects?

Can CoPs make use of metadata over the frontiers of media and standards?

Can we support CoPs by personalized knowledge management and networking strategies in Social Software?

How do adaptive, mobile web-based interfaces for CoPs look like?

Reflective SupportCan CoPs continuously elicit and implement requirements? How much computer science support is needed?

Can CoPs learn meaningful social interaction and make use of disturbances?

How can CoPs record their complex media learning traces and how they can deal with them?

Can CoPs maintain or even improve their agency (Learning, Researching, Working) in the Web 2.0?

Actor-Network Theory

SocialNetwork Analysis

Game Theory



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Solution idea for Reflective Support:Cross-Media Social Network Analysis Interdisciplinary multidimensional model of digital networks

– 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 softwareWiki, Blog, Podcast, IM, Chat, Email, Newsgroup, Chat …

i*-Dependencies(Structural, Cross-media)

Members(Social Network Analysis: Centrality,

Efficiency)

network of artifactsMicrocontent, Blog entry, Message, Burst, Thread,

Comment, Conversation, Feedback (Rating)

network of members

Communities of practice

Media Networks



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Simplified Meta Model

Actor

Member CommunityProcessMedium Artifact

Attribute has

stores creates is affected by belongs go

represents consumes performs ranks

… LocalizeTranscribeBrowse Address

isA

isA

Latour: On Recalling ANT, 1999



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MediaBase Collection of Social Software

artifacts with parameterized 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– Cross-media graphs

Klamma et al.: Pattern-Based Cross Media Social Network Analysis for Technology Enhanced Learning in Europe, EC-TEL 2006



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Media Base Web 2.0 Commander Personalization (user annotates resources with tags and has his page) Community-awareness (resources and annotation of others are open) User-friendly interface (Firefox plug-in, easy insertion of resources, tags, tracking of

recent changes)



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Modeling Dependencies Using the i* Framework

Eric S. K. Yu, Towards Modeling and Reasoning Support for Early-Phase Requirements Engineering, RE 1997

Network

Coordinator

Gatekeeper

Hub

Member

Iterant Broker

URL

isA

isA

isA

isA

Coordination

Artifact

Communication

Legend:AgentGoalResource Task



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Web 2.0 Media Operations in ATLAS



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PALADIN: Disturbances in Cross-media Social Networks

What is a disturbance?– 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



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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.

Disturbance:(EXISTS [medium | medium.affordance = threadArtefact]) &

(EXISTS [troll |(EXISTS [thread | (thread.author = troll) & (COUNT [message | (message.author = troll) & (message.posted = thread)]) > minPosts]) &(~EXISTS[ thread1, message1| (thread1.author1 != troll) &(message1.author = troll & message1.posted = thread1 ]))])])

Forces: medium; troll; network; member; thread; message; urlForce 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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Pattern Discovery ProcessPattern

DisturbanceVariables

Pattern TemplateDisturbance

VariablesPattern Parameters

Pattern Template Instance

Pattern Instance

Disturbance

Variables Pattern Parameters

Forces ForceRelations

Rationale

Dependencies

Description Solution

Pattern Relations

Disturbance Instances

Variables Pattern Parameters

Digital Social Network

1. Set pattern parameters

2. Instantiate disturbances

3. Evaluate disturbances

4a. Change Pattern Parameters

4b. Apply Pattern Solution



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PALADIN Case Study10 patterns of disturbance over 119 social network instances, 17359 individuals, 215 345 mails

Pattern Occurrences RemarksBurst 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.Independent Discussions

13 Occurs in large networks where disconnected subnetworks exist. Scalability is necessary.



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Social Network Analysis of Open Source Communities

Eclipse components network based on analysis of source code repository (Software Architecture)

Eclipse components network based on analysis of mailing list communication (Social Structure)



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Community Reflection about Development Process

Social platform: Eclipse forum eclipsezone Forum: Eclipse communication framework (ECF) Measure: degree centrality Statistics: 225 nodes, 283 edges



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Conversationalist Pattern Social platform: Eclipse mailing list Forum: Device debugging developer discussion



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Questioner Pattern Social platform: Eclipse mailing list Forum: Device debugging developer discussion



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Correlation Estimation between Architecture and Social Structure



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Requirements Reflection Compared to Community Performance

With increasing number of boundary spanners it becomes 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



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Identification of End-Users and Developers in OSS Communities

Community Clustering



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Textual Analysis of Postings from Community Experts

Postings from experts of one of the identified communities



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Knowledge Network of Computer Science with AERCS

Knowledge network to understand major research areas and how theyare 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:- yFiles organic layout (forced-directed paradigm)



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Knowledge Network:the Visualization



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Interdisciplinary Series:Top Betweenness Centrality



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High Prestige Series:Top PageRank



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TeLLNet: SNA for European Teachers‘ Life Long Learning

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?



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eTwinningNetwork Information Visualization

• Teacher network 2008 as example•Cooperation among countries



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Visual Analytics• Labels and dates help to identify complete substructures

• substructures



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Meta Competence Development for TeLLNet



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Network Simulation & Evaluation Network Simulation

Teachers profiles (skills, knowledge, identity) Identification of payoffs and strategies Network formation

Network Evaluation Nash equilibrium (win-win situation) Quality labels



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Conclusions Can CoPs continuously elicit and implement requirements?

– Eclipse case study– 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



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Outlook

Cloud Data Management for Communities– 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– Lesser need for computer science & IT experts