虚拟社区中的推理：人口统计、用户偏好和网络拓扑
Inferences in a Virtual Community: Demography, User Preferences, and Network Topology
摘要：
本文提出了一种计算过程中提取人口数据，挖掘模式的人的喜好，并测量虚拟网络的拓扑结构。该网络是从基于互联网的在线社区的个人和关系数据创建的，其中人被认为是网络中的节点，人与人之间的关系被认为是边。拉古纳是一个社区，其注册的家乡是洛斯巴尼奥斯，拉古纳被用作该方法的测试平台。该方法能够提供关于测试床的以下人口统计、偏好和拓扑结果：（1）女性用户（52.34%）多于男性用户（47.66%）;（2）同质性（即，在用户关于年龄水平的偏好中观察到“物以类聚”（Birds-of-a-feather adage），使得他们强烈偏向于与相似年龄的用户成为朋友;（3）性别偏好中存在异性恋，使得异性用户之间的友谊更经常发生。(4)该网络具有小世界特性，连接用户间的平均路径长度为4.5（最大值为12），小于著名的{ \em六分离度}~ \cite{travers69} ;（5）该网络具有无标度特性，具有重尾幂律分布（幂$λ= -1.02$和$R^2 = 0.84$），表明存在许多用户作为网络枢纽。该方法成功地提供了重要的数据，从一个虚拟的社区，可以使用的几个研究人员在统计，数学，物理，社会科学和计算机科学领域。
英文摘要：
This paper presents a computational procedure for extracting demography data, mining patterns of human preferences, and measuring the topology of a virtual network. The network was created from the personal and relationships data of an online Internet-based community, where persons are considered nodes in the network, and relationships between persons are considered edges. A community of Friendster users whose listed hometown is Los Baños, Laguna was used as a test bed for the methodology. The method was able to provide the following demographic, preferential, and topological results about the test bed: (1) There are more female users (52.34\%) than male (47.66\%); (2) Homophily (i.e., birds-of-a-feather adage) is observed in the preferences of users with respect to age levels, such that they are strongly biased towards being friends with users of a similar age; (3) There is heterophily in gender preference such that friendship among users of the opposite gender occurs more often. (4) It exhibits a small-world characteristic with an average path length of 4.5 (maximum=12) among connected users, shorter than the well-known {\em six degrees of separation}~\cite{travers69}; And (5) The network exhibits a scale-free characteristics with heavily-tailed power-law distribution (with the power $λ= -1.02$ and $R^2 = 0.84$) suggesting the presence of many users acting as the network hubs. The methodology was successful in providing important data from a virtual community which can be used by several researchers in the fields of statistics, mathematics, physics, social sciences, and computer science.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
