中文摘要：

【目的】更好地反映MOOC论坛参与者的活跃水平以及论坛主题的质量,以提高学员的论坛参与度,发挥MOOC社会效应。【方法】提出超网络下＂迭代超中心度＂概念和算法,通过多次迭代,直至收敛,将整个网络的节点考虑在内,以更全面地反映出不同节点的重要性与影响力。【结果】传统网络指标揭示的信息有限,点度小的节点,其重要性与影响力可能大;点度相同的节点,重要性与影响力也会不同。迭代超中心度全面衡量节点的重要性,在MOOC中更能反映出节点推动知识流动的能力。【局限】数据量比较少,只对一门课程进行分析,没有从更多的超网络指标进行分析。【结论】＂迭代超中心度＂可以揭示出论坛参与者的活跃水平以及论坛主题的质量,可以作为一种改进论坛设置的评价指标。

英文摘要：

[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.