基于社会学理论的信任关系预测模型

随着社会网络的盛行，信任作为用户之间交互的基础，在信息共享、经验交流和社会舆论方面发挥着重要作用。然而，信任是一个复杂而抽象的概念，受多种因素影响，很难识别信任形成的诱因以及其形成机制。由于来自社会科学的社会学理论有助于解释社会现象，而社会网络反映了现实世界中用户之间的联系，因此，从社会学角度出发，通过研究社会等级理论和同质性理论获取信任关系的发展规律，进而构建信任关系预测模型。首先，对社会等级理论和同质性理论进行阐述，并验证了社会等级理论和同质性理论在社会网络中的存在；然后，分别针对社会等级理论和同质性理论对信任关系的影响提出社会等级正则化方法和同质性正则化方法；最后，利用非负矩阵的三维分解方法并结合社会等级理论和同质性理论实现对信任关系预测的建模，并提出 SocialTrust 模型用于信任关系预测。实验结果表明，相比于其他方法，该方法在信任关系预测方面具有较高的精度。

Trust Prediction Modeling Based on Social Theories

With the pervasion of social media, trust, as the basis of human interactions, has been playing an important role in addressing information sharing, experience communication, and public opinions. However, trust is a complex and abstract concept influenced by many factors, and it is difficult to identify the inducing factors and analyze the formation mechanism. Recognizing that social theories from social sciences are helpful to explain social phenomena, and social networks reflect user correlations in real world, this paper investigatethes trust prediction problem from the perspective of social science, and constructs trust prediction model by studying the disciplines of trust relations occurring and developing based on social status theory and homophily theory. Firstly, it gives a brief introduction to social status theory and homophily theory, and verifies the existence of social status theory and homophily theory in social networks. Then, it proposes social status regularization and homophily regularization according to the effects of social status theory and homophily theory in predicting trust relations. Lastly, it models trust prediction by incorporating non-negative matrix tri-factorization, social status theory and homophily theory, and establishes trust prediction model SocialTrust. Experimental results demonstratethe effectiveness of the proposed method in trust prediction with a higher accuracy than other baseline methods.