Abstract: 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.

Key words:  , SALSA algorithm； social network； key node； SIR model