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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (8): 1-8    DOI: 10.11925/infotech.2096-3467.2017.08.01
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Analyzing Interaction of MOOC Users with Iteration Super Centrality
Jiang Wu(),Chaocheng He,Panhao Ma
School of Information Management, Wuhan University, Wuhan 430072, China
Center of Chinese E-commerce Research and Development, Wuhan University, Wuhan 430072, China
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Abstract  

[Objective] This paper evaluates the activity level of the MOOC forum participants and the quality of the forum themes, aiming to improve the participation of the forum users and increase their social impacts. [Methods] We proposed a new concept and algorithm based on “Iterative Super Centricity” with several iterations till convergence. We used nodes of the entire network to determine their importance and influence. [Results] The proposed ISCen (Iterative Super Centrality) algorithm could measure the importance of nodes and their ability to disseminate knowledge. [Limitations] We only examined one course and did not analyze those super-network indicators. [Conclusions] “Iterative Super Centrality” can reveal the activity level of the forum participants and the quality of the online contents, and then improve the MOOC services.

Key wordsMOOC      Forum      Super-network      Iterative Super Centrality      Knowledge Flow     
Received: 31 May 2017      Published: 28 September 2017

Cite this article:

Jiang Wu,Chaocheng He,Panhao Ma. Analyzing Interaction of MOOC Users with Iteration Super Centrality. Data Analysis and Knowledge Discovery, 2017, 1(8): 1-8.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.08.01     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I8/1

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