[1]许 睿,李艳翠,訾乾龙,等.虚拟学习社区中意见领袖识别模型研究[J].计算机技术与发展,2020,30(05):56-60.[doi:10. 3969 / j. issn. 1673-629X. 2020. 05. 011]
　XU Rui,LI Yan-cui,ZI Qian-long,et al.Research on Identifying Model of Opinion Leader in Virtual Learning Community[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2020,30(05):56-60.[doi:10. 3969 / j. issn. 1673-629X. 2020. 05. 011]
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虚拟学习社区中意见领袖识别模型研究()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年05期
页码:
56-60
栏目:
智能、算法、系统工程
出版日期:
2020-05-10

文章信息/Info

Title:
Research on Identifying Model of Opinion Leader in Virtual Learning Community
文章编号:
1673-629X(2020)05-0056-05
作者:
许 睿; 李艳翠; 訾乾龙; 李宗儒; 张平川
河南科技学院 信息工程学院,河南 新乡 453003
Author(s):
XU Rui; LI Yan-cui; ZI Qian-long; LI Zong-ru; ZHANG Ping-chuan
School of Information Engineering,Henan Institute of Science and Technology,Xinxiang 453003,China
关键词:
意见领袖; 识别模型; 中心性; 虚拟社区; K-means 算法
Keywords:
opinion leader; recognition model; centrality; virtual community; K-means algorithm
分类号:
TP319
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 05. 011
摘要:
虚拟学习社区是传统教育突破空间资源限制形成的便捷性学习环境,其中意见领袖是构成社区信息通路的重要角色，对其他用户有强大的影响力。 为了准确识别社区中的意见领袖，构建出虚拟学习社区网络,分析各用户的中心性和社会网络角色特征,选取入度、出度、介数、特征向量中心性、用户活跃度、用户帖子转发量、用户帖子评论量等七个特征值作为筛选条件,结合基于 K-means 的用户聚类算法,提出基于 K-means 算法的意见领袖识别模型。 最后,将该识别模型应用于某虚拟社区,根据各个聚类子类的特征向量,提取理论意义上的意见领袖集合。 实验证明, 获取意见领袖集合具有很高的准确性,识别出的意见领袖均处于中心者或桥梁位置,占据着社会网络的优势位置,在虚拟社区中承担着核心或中介等特殊作用。
Abstract:
Virtual learning community is a convenient learning environment which breaks through the limitation of traditional educational space resources. Opinion leaders play an important role in the formation of community information channels and have a strong influence on other users. In order to accurately identify opinion leaders in the community,we construct a virtual learning community network,analyze the user-centered and social network role characteristics,and select in degree,out degree,betweenness centrality,eigenvector centrality,user activity, the amount of user posts forwarded,number of comments on user posts as screening conditions. Based on K-means user clustering algorithm,an opinion leader recognition model based on K-means algorithm is proposed. Finally,we use the model to process a virtual community, and extract the theoretical opinion leader set according to the feature vectors of each clustering subclass. Experiment shows that the collection of opinion leaders has high accuracy,and the identified opinion leaders are in the center or bridge position,occupying the dominant position of social network,and playing a special role of core or intermediary in the virtual community.

相似文献/References:

[1]俞淮 郑倩冰 毛羽刚 朱培栋.基于局部中心度的在线论坛意见领袖发现算法[J].计算机技术与发展,2012,(04):9.
　YU Huai,ZHENG Qian-bing,MAO Yu-gang,et al.An Algorithm for Online Forum Opinion Leaders Discovery Based on Local Centrality[J].COMPUTER TECHNOLOGY AND DEVELOPMENT,2012,(05):9.
[2]申 彦,刘春华.基于在线品牌社区意见领袖的用户关键需求挖掘[J].计算机技术与发展,2024,34(02):23.[doi:10. 3969 / j. issn. 1673-629X. 2024. 02. 004]
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更新日期/Last Update: 2020-05-10