基于距离模型的用户关系强度评估

摘要

对微博用户关系强度的评估是分析和研究微博网络的基础。文章提取微博用户的个人基本信息、交互信息、互粉信息，并提出一种基于距离的评估模型对微博用户的关系强度进行准确的评估分类，该距离模型根据三种假设，得出最基础的用户关系强度群，然后根据距离函数对未知的关系强度进行分类。由此得出一张有向加权图，节点表示微博用户，边表示用户之间的关注关系，权值表示微博用户之间的关系强度。将该距离模型得出的预测结果和采用对用户相对交流值，用户背景的相似度和用户是否互粉三种属性值进行加权融合得出的实验结果进行比较分析可得出：该评估模型能够结合用户的综合信息评估出用户之间的关系强度，结果全面、准确、直观，也充分说明该模型既吸取了加权融合法的优点，也避免了加权融合的弊端，很好的体现了机器学习的优势，为微博舆论的研判提供最直接的参考依据。%Evaluation of user relationship strengths of Microblog is a basis for analysis and research of Microblog network. This paper fetches personal information, mutual information and fans information of Microblog users, puts up with a distance-based evaluation model to accurately evaluate and classify the relationship strengths between Microblog users. The model based on three assumptions, draw up the most basic user relationship strengths group, and then the relationship between the intensity of the unknown are classified according to the distance function. Compared the predictions derived from the model and result which derived through three attribute value weighted fusion: the relative exchange value of the user, the user background similarity and whether the usermutual followed, we can infer that with comprehensive, accurate and visible results, the model can evaluate the relationship strengths between users combined with their general information, andindicates that this model both combines the advantages of weighted fusion method and avoids the disadvantages of the weighted fusion, which indicated the advantages of machine learning, which provides the most direct references for studying and judging Microblog comments.