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Virtual Neighborhoods Architecture of Online Communities . Reuven Aviv Zippy Erlich Gilad Ravid Agenda. Introduction Design, Mechanisms, Architecture Method Results. Design of network. mechanisms. Social Interdependence theory.

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virtual neighborhoods architecture of online communities

Virtual Neighborhoods Architecture of Online Communities

Reuven Aviv

Zippy Erlich

Gilad Ravid

  • Introduction
  • Design, Mechanisms, Architecture
  • Method
  • Results

Design of network


Social Interdependence theory

Matching the predictions of network emergence theories


Content Analysis

Network statistical analysis of Markov models

Collaborative Knowledge construction

sna viewpoints
Global SNA



Equivalence (role groups)

Power of actors

Range of influence


Local SNA



Dyads and triads

SNA viewpoints

Aviv, R., Erlich, Z., Ravid, G., & Geva, A. (2003). Network Analysis of Knowledge Construction in Asynchronous Learning Networks. Journal of Asynchronous Learning Networks

the social capital mechanism
The Social Capital Mechanism
  • Hunt for Knowledge (social capital)
    • Using efficient interactions
    • E.g. bridging others
  • Community works with broadcast medium:
    • Most efficient connection: No interactions
      • Passive members (Lurkers)

Cognitive balance

Emergence of transitive triads



Creation of knowledge support

The architecture of a network can be describes in terms of three components
    • One or more relations are the fundamental glue between the actors
    • A partition of the actors and the relations into 2 level hierarchy of groups of actors
    • A set of mechanisms shaping the relations to the creation of the neighborhood
virtual neighborhoods


In star

Mutual dyad

Mix star

Out star

Virtual Neighborhoods

Transitive triad

Cyclic triad

method of analysis
Method of Analysis
  • Reveal Architectural Components
  • Identify Relevant Theories
  • Identify Mechanisms
  • Analyze the recorded responsiveness data of two online forums of learners with different design
example two communities
Example: Two Communities
  • 16 weeks each; 19, 18 participants
  • Parts of Open U “Business Ethics” Course
  • Team community
    • Designed for Knowledge Construction
    • Tested positively by Content Analysis
  • Forum Community
    • Designed for support by Q & A
social capital transaction costs
Social Capital & Transaction Costs
  • Burt 1992, 2002
  • Bridge over Holes with minimal cost
  • Few single links
  • link<0
  • Supported for both networks
collective action
Collective action
  • Coleman, 1973, 1986; Marwell & Oliver 1993; Fulk et al. 1996
  • Inducements to contribute under peer pressure
  • Respond to several others
  • If large density & centralization & size then out star > 0
  • Supported for team network.
  • Not supported for forum network because condition in not fulfilled
  • Willer & Skvoretz, 1997; Hommans, 1958
  • Exchange resources directly, depending on partner & network status
  • Tendency to reciprocate to resource promising partners
  • mutuality > 0
  • Not supported for team network because there are no a-priory resource promising actors
  • supported for Forum network because Tutor is a-priory resource promising actors
generalized exchange
Generalized exchange
  • Bearman, 1997
  • Exchange resources via mediators, depending on partner & network states
  • Tendency to respond cyclically to resource promising partner
  • cyclicity > 0
  • Not supported in both networks. Probably because no need for information exchange via mediators
contagion exposure
Contagion Exposure
  • Burt 1980; Contractor et al., 1990
  • Leading to social influence & limitation in attitudes, knowledge & behavior
  • Respond to same as other equivalent actors
  • Out star > 0; in star > 0; mixed star >0; transitivity >0
  • Not supported in both networks. Probably because contagion process could not develop in the short lifetime of networks
cognitive consistency
Cognitive Consistency
  • Heider 1958; Festinger, 1957; Cartwright et al., 1956
  • Drive for balance in cognitions
  • Respond via several paths
  • transitivity > 0
  • Supported in team networks. Not supported in the forum network. In both networks this is due to their designs
uncertainty reduction
Uncertainty reduction
  • Berger 1987
  • Reduce uncertainty by gaining
  • Attract responses from several others
  • In star > 0
  • Not supported in both networks. In the forum network the tutor clarified all uncertainties
exogenous factors
Exogenous factors
  • Residual personal tendencies o respond or trigger only to actors with pre assigned roles
  • For students (1)resp=0; (2)trigg=0; For tutor (3)resp>0; (4)trigg>0
  • 1,2 supported for both networks; 3 un supported for team network, supported for forum network; 4 un supported for both networks
thank you

Thank You

Questions? Comments? Remarks ?