Chais, Feb. 2006Communities1 Mechanisms of Internet-based Collaborations Complex Network Analysis Approach Reuven Aviv, Chais Research Center & Department of Computer Science Open University of Israel

Chais, Feb. 2006Communities2 Context: online communities as networks Like Social Networks –advice, command, Like Web-pages, gene networks, etc.. Trigger/Response Network

Chais, Feb. 2006Communities3 Research Question Are Learning Communities Social Networks? Method  Identify Social Network mechanisms underlying responses in the communities Answer Yes and No Why is it important?  Implications on design features

Chais, Feb. 2006Communities4 Social Network Mechanisms (1) 1. Hunt for social capital (knowledge) Use efficient connections (e.g. bridge) If communication is broadcast efficiency: wait for others to respond Result: Passive community 2. Exchange mechanism Exchange responses with potential responders (requires interdependence) Result: reciprocal events ji

Chais, Feb. 2006Communities5 Examples of Social Network Mechanisms (2) 3. Theory of Cognitive Balance Drive for Cognition Balance all understand the same way goals, concepts, problems, solutions (requires set goal and commitment) Result: multiple communication paths clustering events (basic block of cohesiveness) i k j

Chais, Feb. 2006Communities6 Results Hunt for social capital: underlies all social networks and online learning communities –does not lead to responsive community Exchange: underlies all social networks and online learning communities Cognition Balance: common in social networks, but does not develop in online learning communities Implications for design?

Chais, Feb. 2006Communities7 Method: Motif Analysis Random Graph Model creates ensemble of networks (by simulation) Identify Motifs: events (e.g. reciprocity) occurring above occurrence in the ensemble

Chais, Feb. 2006Communities8 Motifs and Mechanisms in other areas Gene Regulation, Neurons –Feed-Forward loop –Stimulus WWW network –Clustering of pages –Drive for shortcuts Food Webs Communities –Bi Parallel structures –Energy flow mechanisms i kj i kj i k j i

Chais, Feb. 2006Communities9 Analysis of online learning communities 97 online communities 40 social networks Four baseline Random Graph Models: Network Events: Reciprocity, Clustering Are these motifs?

Chais, Feb. 2006Communities10 Results: the reciprocity motif

Chais, Feb. 2006Communities11 Online networks: clustering is not a motif Social Networks: clustering is (in many networks) a motif

Chais, Feb. 2006Communities12 Implications: design features Exchange mechanism Exchange responses with previous or potential responders requires interdependence ji Drive for Cognition Balance Clustering of responses Basic block of cohesiveness requires set goal and commitment i k j

Chais, Feb. 2006Communities13 Discussion Practical implications –Can be done in real time –Identify design problems What’s next? –Time dependence –Compare Social, Biological networks –Association with personal attributes More …

Chais, Feb. 2006Communities14 Thank You

Chais, Feb. 2006Communities15 Details of this research Response Neighborhoods in Online Learning Networks: A quantitative Analysis (Journal of Educational Technology & Society, 8(4), 2005) Reciprocity & Transitivity Analysis of Online Learning Networks (submitted to Connections) –Preprints Available