The relationships between positive （negative） eigenspectrums and the structure properties of community （anti-community） of complex networks are investigated, and some corresponding definitions are given. By using the multieigenspectrums of modularity matrix of networks, a kind of structural centrality measure called the community centrality, is introduced. This individual centrality measure describes the strength that the individual adheres to the corresponding community. The measure is illustrated and compared with the standard centrality measures using several artificial networks and real world networks data. The results show that the community centrality has better discrimination, and it has positive correlation with the degree centrality.