以开心网15个大学群为案例,应用信息熵和度分布两种方法,研究了社会性网络服务社区中人际节点空间分布特征及其地缘因素的影响。人际节点是以"好友"关系建立的链接来表达的,研究数据包括通过"成员"体现的好友和通过"话题"体现的好友2个层次,以便可以将虚拟的可能关系变为虚拟现实的确定关系。研究结果如下:①各大学群中好友空间分布信息熵值均较低,即空间分布不均匀,具有显著的集中性,这种非均匀性与城市经济规模有关。②多数大学群中好友空间分布符合度分布模型,随距离的增加而衰减,并具有明显的本地集中特征。③大学群中好友空间分布的本地集中性体现出地缘因素的作用,信息时代地缘因素依然影响着人际节点空间关系的存在形式。

From the geographical perspective,this study aims to explore the spatial distribution characteristics of interpersonal nodes in social networking services community.In order to study the the spatial distribution characteristics of interpersonal nodes and geographical factors in the social networking services community,15 university groups in Kaixin Net are choosen as samples.Two methods of comentropy and degree distribution are used in this study,and the curve model of information flow distance decay of the university groups in Kaixin Net can be evaluated by using Origin.The study findings are: 1) The evenness degree of friends’spatial distribution in university groups of kaixin can be reflected by the size of comentropy value.The lower the comentropy value of spatial distribution of interpersonal nodes is,the more concentrated of the relationship of interpersonal nodes.The comentropy values of friends’spatial distribution in university groups are lower,and the spatial distribution presents two basic characteristics: on the whole,the distribution of friends is not even with significant concentration.The unevenness distribution of friends has a negative correlation with the city economic scale.The economic scale in Shanghai is the highest,and the comentropy value is the lowest.It suggests that the evenness degree of the friends’spatial distribution in this university groups is the lowest,and concentration degree is the highest.This relates to the gravity of economic scale towords people and information flow. 2) The friends spatial distribution in most university groups is fit with the degree distribution-exponential distribution model.Chi2/DoF value in each university group is far less than the critical value of 2,and t values are all bigger than critical value.The R2 of most university groups are more than 0.9.All of these show an obviously degree distribution-exponential distribution.The distribution of the number of friends presents a decay with distance.The higher of the decay coefficient,the stronger distance sensitivity of the distribution of the number of friends is.The friends of the university groups are centralized distribution in the local,and have significant local concentration characteristics.3) In the real world,the establishment of interpersonal node relationship is largely influenced by geopolitical factors.But with the emergence of virtual communities,the interpersonal relationships based on distance constraints have been breakthrough by instant access platform of social network. It will create new human spatial relationships.The local concentration characteristics of friends’spatial distribution in the university groups are related to the geographical factors.The human virtual activity still has historical heredity,and the local concentration characteristic can be explained by geographical factors.Based on geographical factors,the closer of the people,the stronger trust is in them,and easier to establish a relationship. The network users are tend to connect with the people close to them,so the interpersonal node relationship of university group in Kaixin Net presents the local concentration characteristic.In the information age,spatial relationship of interpersonal nodes is still influenced by geographical factors.The restriction of space and the non-restriction of space-time and communication are coexisting in social networking service community.