KASW'08 - Invited Talk

Ralf Klamma RWTH Aachen University KASW Workshop, I-Media, September 3, 2008 Community-Oriented Knowledge Acquisition and Analysis

Agenda
Media & Knowledge
Communities
Case Studies
Disturbances
Scientific Communities
Community Measures
Conclusions & Outlook
Agency & Patienthood in Digital Networks

Learning & Knowledge Management Individual / Community Perspective [Nonaka & Takeuchi, 1995] [Ullman, 2004] Semantic Knowledge semiotic concepts documentation Verbal words linguistic data Non-verbal image, icon, index video blogs, diagrams, images, photographies Episodic Knowledge memory of experiencing past episodes web blogs, narratives Declarative Knowledge Procedural Knowledge sensomotoric skills, procedural scripts non-documented routines and operations

Semiotics in the Tradition of Ferdinand de Saussure (1957 - 1913) comprehension / articulation activation of community information system human neural network Artifacts of community information system in presentia in absentia performance Parole competence Langue

Hypotheses 1. A semiotic knowledge system is dynamic and it changes every time it is activated. 2. The meaning of a concept is determined by how it interacts with other concepts and by how it can be distinguished from other concepts in the knowledge system. (Positive and Negative Knowledge) 3. The knowledge system is carried by a material medium. The modality of the medium influences knowledge structures.

Cross-Media Theory of transcription Pre-“texts“ Transcript Cross-Media Transcription Understand and Criticize Jäger, Stanitzek: Transkribieren - Medien/Lektüre 2002
Strategies of transcriptivity
Collection of learning materials are re-structured by new media
Design is specific for media and communities by default
Strategies of addressing
Social Software promotes the globalization of address spaces
Personalization and adaptive strategies are mission critical for CoPs
Strategies of localisation
Re-organization of local practices is stimulated by new media like Social Software
Need to model practice explicitly

Babylonian Talmud: A very old Hypertext
Scroll/book/printed book
Talmud schools (Jeshiwot)
Authoritative knowledge source
Dialogic encyclopedia
Structure of complex texts
Connected knowledge
Transcribe?
Address? Localize?

CESE: Multi-lingual Cross-Media System Published in: DS-NELL 2000, ICALT 2002, ICWL 2002, WWW 2003

Research Approach: Reflective Learning Network Collaborative adaptive learning network Mining tools for Communities Measure, Analyse, Simulate Social Software Development Assessment requirements for Communities Support evolving learning communities (repeated assessment of community requirements) Based on Preece 2001, cf. I-KNOW 2006 for details

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 software
Wiki, Blog, Podcast, IM, Chat, Email, Newsgroup, Chat …
i*-Dependencies (Structural, Cross-media) Members ( Social Network Analysis : Centrality, Efficiency) network of artifacts Microcontent, Blog entry , Message, Burst, Thread, Comment, Conversation, Feedback (Rating) network of members Communities of practice Media Networks

Simplified Meta Model for ANT using Latour Actor Attribute has isA isA Latour: On Recalling ANT , 1999 Klamma, Spaniol, Cao: A model for social software, IJKL 2007 Member Network Learning Service Medium Artifact stores creates is affected by belongs go represents consumes performs ranks … Match Retrieval Browse Search

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 Coordination Artifact Communication isA
Legend:
Agent
Goal
Resource
Task

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

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[ thread 1 , message 1 | (thread 1 .author 1 != troll) &
(message 1 .author = troll & message 1 .posted = thread 1 ]))])])
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.

Pattern Discovery Process Digital Social Network 1. Set pattern parameters 2. Instantiate disturbances 3. Evaluate disturbances 4a. Change Pattern Parameters 4b. Apply Pattern Solution Pattern Disturbance Variables Pattern Template Disturbance Variables Pattern Parameters Pattern Template Instance Pattern Instance Disturbance Variables Pattern Parameters Forces Force Relations Rationale Dependencies Description Solution Pattern Relations Disturbance Instances Variables Pattern Parameters

PALADIN Case Study 10 patterns of disturbance over 119 social network instances, 17359 individuals, 215 345 mails Occurs in big networks where the members are distributed in different clusters. 40 No Leader Occurs for members having neighbors with only one contact. 67 Structural Hole Occurs in large networks where disconnected subnetworks exist. Scalability is necessary. 13 Independent Discussions The pattern occurs in the network centered around a member. 37 Leader Spammers can be found often in discussion groups. False positives exist. 86 Spammer Troll occurs very rarely in cultural communities. True negatives exist. 2 Troll Occurs in small networks. The effects of the lack of an answering person must be further checked with content analysis. 61 No Answering Person The existence implies that the network is not popular. 67 No Questioner The existence implies little communication in the network. 76 No Conversationalist The pattern finds out topics which were very important for certain period of time. Scalability is necessary. 22 Burst Remarks Occurrences Pattern

Impact of research community on individuals
Academic event modeling
Unstructured data of academic events
Diversity of additional media: Photos, Videos, Blogs, Wikis…
=> A model for academic events and their communities documentation
Events recommendation tool for researchers
Design a community based recommendation algorithm
Events communities analysis and visualization.
Community analysis from community of practice point of view

AERCS: Evolution of Scientific Communities

Evolution of community VLDB 1990 VLDB 1995 VLDB 2000 VLDB 2006

Community visualization – ACM SIGMOD example ACM SIGMOD

Models of Community Success
Reference Model: D&M IS Success Model (1992)
Based on >100 Empirical/Conceptual Studies
Validated by Independent Studies Updated
Model: Integration of Current Concepts
Mobility (Mobile Context)
Multimedia Communities

Success Classiﬁcation & Measurement
Quantitative: Monitoring User-Service
Communication Logging
Mobile Context Information
MobSOS Monitoring Module
Quantitative & Qualitative: Survey
Online User Surveys (Questionnaire)
MobSOS Survey Module
Subjective Objective Quantitative Monitoring Survey Qualitative Survey

MobSOS Monitoring Module
Client: Capture & Transmit Mobile Context Information
Testbed: Log Communication & Mobile Context

Mobile Service Oracle for Success
Monitoring of service invocations
Time and position tracking of a service call
Recognition of patterns in user behaviour

Storytelling Expertfinding
New Measure for Knowledge in a Community
Expert value Mean: 0,2624 # Entries: 99.778 Frequency

Story-tellling Expert Finding Keywords Expert values
Knowledge Value of Community sorted by keywords
# Recommendations Expert Amateur

Conclusions
Media and Communities shape knowledge structures
Semiotic systems depend on media
Communities set goals and means
Case Studies
Social Patterns in Communities
Evolution of Scientific Communities
Community Success Models
Expert finding in Communities
Further research
Uncertainty in Tagging systems
Continuous elicitation of community needs
Emotional dimension of collective intelligence

KASW'08 - Invited Talk

by Ralf Klamma

Accessibility

Categories

Upload Details

Usage Rights

2 Embeds 10

Statistics

KASW’08 - Invited Talk Presentation Transcript

http://beamtenherrschaft.blogspot.com	9
http://eduspaces.net	1