基于拓扑势熵的维基百科词条编辑演化研究

Article Edit Evolution in Wikipedia Based on Topology Potential Entropy

网络群体智能涌现问题是信息科学和社会科学的多学科交叉研究问题。基于映射思想将其映射为维基百科词条编辑演化问题,提出词条编辑演化研究方法框架;以维基百科高质量词条编辑历史数据为数据集,以编辑者为节点,以编辑者间编辑交互关系为连边,构建词条编辑交互网络,通过建立网络演化测度拓扑势熵实现对词条编辑演化研究。实验分析表明,网络结构和词条总体上朝着有序方向演化,演化呈现出"从注重完整性到注重准确性再到注重可读性"的由低到高3个阶段,直至群体结构趋于稳定,结构具有无标度性,词条质量和群体智能达到很高水平;存在语量与语义之间此消彼长、最终达到动态平衡的过程,语量与语义平衡临界点近似为黄金分割点,词条编辑演化遵循着黄金分割律。方法框架有效,深化了对词条编辑演化、网络群体智能和社会计算的认识。

The emergence of web collective intelligence is an interdisciplinary research topic involving information science and social science. The topic is mapped to the problem of article edit evolution in Wikipedia based on mapping idea, then the framework of article edit evolution is proposed, the article edit interaction networks are constructed based on the history data of the featured articles in Wikipedia; in the networks, a node is editor and a link is the edit interaction connection between editors. The topology potential entropy is developed to study the article edit evolution. Results show that networks structure and articles evolve toward the orderly direction; the evolution has experienced three development stages from low to high with the emphasis on integrity, accuracy, and readability. The collective structure gradually becomes stable, and it has a scale-free property, both article quality and collective intelligence reach at a high level. There is a process from seesaw-like complementarity to dynamic balance between word quantity and word meaning, the critical point of balance is closed to the golden section point; article edit evolution follows the golden section law. The framework is effective, and the research deepens the knowledge of article edit evolution, web collective intelligence, and social computing.