1. A method for classifying an object based on a social networking service, the method being run in a computing device, and the computing device comprising a storage apparatus, one or more processors, and program instructions stored in the storage apparatus and executed by the one or more processors, the method comprising: acquiring feature information of an object, the feature information comprising multiple segmented words; computing a semantic vector of the feature information, the semantic vector being used to reflect a relevancy feature when the segmented words exist in the feature information simultaneously; inputting the semantic vector of the feature information of the object to a predetermined classifier, to obtain an initial category of the object after the object is classified; wherein the object comprises a user and/or a group, and after the computing a semantic vector of the feature information, the method comprises: determining, for each object by using a semantic vector of feature information of the object, a predetermined number of similar objects corresponding to the object; forming an object pair by using the object and each of the similar objects; constructing a bipartite graph by using the object pair and a correspondence between a group and each user in the group; and clustering an object in the bipartite graph by using a topic modeling algorithm, wherein the bipartite graph at least comprises a correspondence formed by a first element and a second element; and when the first element in the correspondence is a group, the second element is a user in the group or a group that is in a same object pair of the group; or, when the first element in the correspondence is a user, the second element is a user that is in a same object pair of the user.