基于SALSA的社交网络重要节点发现算法

社交网络中重要节点的发现研究具有较大的实际意义与价值。考虑社交网络中用户作为节点所包含一些特有的属性，通过将用户的社交行为划分强/弱关系的方式对社交网络拓扑结构的关系边进行补充，提出一种基于SALSA算法的加权算法WSALSA来发现社交网络中的重要节点。采用部分新浪微博真实数据进行实验及验证，对比PageRank、HITS和SALSA算法得到的节点影响力排序结果在SIR模型中的传播能力，结果表明WSALSA算法与SIR排序结果的斯皮尔曼相关系数值更高，对社交网络中节点重要性的评估更加准确。

Algorithm for Discovering Key Nodes in Social Networks Based on SALSA

The study of finding key nodes in social networks is of great practical significance. Considering the behaviors of user nodes in social networks, this paper divides users’ social behavior into strong/weak relationships to supplement the relationship edge of social network topology. And combined with the ideas of SALSA algorithm, this paper proposes a weighted algorithm WSALSA to discover key nodes in social networks. Through a large number of experiments and verifications with Sina Weibo dataset, we compare spreading effects of PageRank, HITS and SALSA algorithms’ results in the SIR model. The experimental results show that the weighted WSALSA key nodes discovery algorithm has a higher Spearman’s correlation coefficient with SIR ranking results. Therefore, the weighted WSALSA algorithm has higher accuracy in the evaluation of the importance of nodes in social networks.