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Wang et al. Gabrys, R. Howlett, and L. Jain Eds. Corchado et al. Rutkowski et al. Tiwari et al. Gavrilova et al. Gelbukh Ed. When applied to CSCL, SNA is used to help understand how learners collaborate in terms of amount, frequency, and length, as well as the quality, topic, and strategies of communication. It uses graphical representations, written representations, and data representations to help examine the connections within a CSCL network. The focus of the analysis is on the "connections" made among the participants — how they interact and communicate — as opposed to how each participant behaved on his or her own.
There are several key terms associated with social network analysis research in computer-supported collaborative learning such as: density , centrality , indegree , outdegree , and sociogram. Researchers employ social network analysis in the study of computer-supported collaborative learning in part due to the unique capabilities it offers. This particular method allows the study of interaction patterns within a networked learning community and can help illustrate the extent of the participants' interactions with the other members of the group.
Some authors also suggest that SNA provides a method of easily analyzing changes in participatory patterns of members over time. The findings include the correlation between a network's density and the teacher's presence,  a greater regard for the recommendations of "central" participants,  infrequency of cross-gender interaction in a network,  and the relatively small role played by an instructor in an asynchronous learning network.
Although many studies have demonstrated the value of social network analysis within the computer-supported collaborative learning field,  researchers have suggested that SNA by itself is not enough for achieving a full understanding of CSCL. The complexity of the interaction processes and the myriad sources of data make it difficult for SNA to provide an in-depth analysis of CSCL.
This can be referred to as a multi-method approach or data triangulation , which will lead to an increase of evaluation reliability in CSCL studies. From Wikipedia, the free encyclopedia. This article is about the theoretical concept. For social networking sites, see social networking service. For other uses, see Social network disambiguation.
Metrics Algorithms. This section may require cleanup to meet Wikipedia's quality standards. The specific problem is: More careful cleanup after merge required Please help improve this section if you can. December Learn how and when to remove this template message. See also: Social network analysis criminology. Actor-network theory Community structure Complex network Digital humanities Dynamic network analysis Friendship paradox Individual mobility Mathematical sociology Metcalfe's law Network-based diffusion analysis Network science Organizational patterns Small world phenomenon Social media analytics Social media mining Social network Social network analysis software Social networking service Social software Social web Sociomapping.
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Oxford: Oxford University Press. Transitivity, homophily, and the need for network closure". Journal of Personality and Social Psychology. Morgan Kaufmann. Social Networks Analysis: Methods and Applications. Cambridge: Cambridge University Press. A short, clear basic summary is in Krebs, Valdis Internet Protocol Journal.
Social Networks. Field Manual Counterinsurgency. Headquarters, Department of the Army. B—11 — B— This wiki site provides numerous examples and a tutorial for use with R. White In Thai, My T.
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Link from Stanford University. Field Methods. Measuring influence on Twitter. Measuring user influence on Twitter: A survey. The Changing Roles of Advertising. Retrieved 22 October Analyzing the Social Web. Journal of Internet Services and Applications. The Guardian. Retrieved 19 July Retrieved 19 Jul Natural Language Engineering.
Global Networks. What is Twitter, a social network or a news media? O'Connor-Divelbiss eds. Fourth International Conference of the Learning Sciences. Mahwah, NJ: Erlbaum. Documenting Collaborative Interactions: Issues and Approaches. Social information sharing in a CSCL community.
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