基于k-派系过滤算法的高校社团结构分析  

Analysis of University Associations Structure Based on k-clique Percolation Algorithm

作　　者：王烽 陈如梦 胡枫 WANG Feng;CHEN Rumeng;HU Feng(Computer College,Qinghai Normal University,Xining 810008,China;The State Key Laboratory of Tibetan Intelligent Information Processing and Application,Xining 810008,China;Academy of Plateau Science and Sustainability,Xining 810016,China)

机构地区：[1]青海师范大学计算机学院,青海西宁810008 [2]藏语智能信息处理及应用国家重点实验室,青海西宁810008 [3]高原科学与可持续发展研究院,青海西宁810016

出　　处：《运筹与管理》2024年第9期113-119,共7页Operations Research and Management Science

基　　金：国家自然科学基金资助项目(61663041);青海省自然科学基金资助项目(2023-ZJ-916M)。

摘　　要：高校学生社团中的重叠结构代表社团之间的交叉渗透,从重叠结构的角度研究高校社团之间的交叉渗透是一个值得探索的问题。本文以在校学生为节点,同一社团内的学生相互连接为边,构建高校社团网络,利用k-派系过滤算法实现重叠结构检测及社团的划分,并在此基础上,结合k的不同取值、复杂网络以及超网络的部分指标进一步分析网络中的重叠关系。通过将k取不同值时未丢失节点数量的比值、社团划分数量和模块度Q值与高校社团实证数据集的实际划分结果进行对比分析,验证了该算法的有效性,得到了k的最佳取值。本文有助于分析高校社团的结构、特点,进一步,分别从重视学校的引导作用、加强社团人才文化建设、参加社团避免盲从这三方面提出了社团建设的指导性建议,为高校社团的建设及大学生选择社团提供了理论依据,且具有一定的现实意义。In most real-world networks,there are no completely independent community structures,and they are usually made up of many intertwined and overlapping communities.An overlapping community structure refers to nodes that can belong to multiple different communities at the same time.For example,in a scientific collaboration network,some scientists may be both biologists and mathematicians.If we classify this network according to different disciplines,the same individual may be assigned to two different communities.In university student associations,some students participate in multiple associations,so as to be categorized into various communities.University student associations have the following characteristics:First,there are many organizations with a wide variety and large number of participants.Second,associations are becoming increasingly diverse.Different students’interests and hobbies are quite different,forming a wide range of university associations.Third,each organization establishes its own rules and regulations,with a more systematic management approach.The overlapping structures within university student associations represent the cross-penetration between communities.Studying the cross-penetration of university organizations from the perspective of the overlapping structure is a worthwhile topic to explore.Based on this,this paper collects a total of 6,580 data points on university students’participation in associations through surveys,QR code scanning,and hyperlinks.It removes responses from individuals who do not participate in any associations and those who have no common associations with any classmates,resulting in 5,040 valid data points.Each university student is treated as a node,and since students within the same organization know each other,a fully connected network of nodes belonging to the same organization is formed,creating edges for the network and constructing the university organization network.Using the k-clique percolation algorithm,we perform the overlapping structure detection a

关 键 词：重叠结构 高校社团 k-派系过滤算法 复杂网络 超网络 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]