A processor-implemented method for managing an unsuccessful communication session initiated by a source user to a target user, the method comprising: determining a plurality of correlative contacts between the source user and the target user from one or more communication platforms connecting the source user and the target user, wherein a correlative contact is a mutual contact of both the source user and the target user; scoring the plurality of correlative contacts based on one or more proximity parameters among the source user, each of the plurality of correlative contacts, and the target user, wherein the proximity parameters include information describing a level of acquaintance and/or geographical coincidence of the source user, target user and/or correlative contacts, and wherein scoring comprises assigning a primary weight to each of the one or more proximity parameters using a machine learning algorithm and computing a weighted average of the one or more proximity parameters for each of the plurality of correlative contacts; generating an initial set of correlative contacts from the plurality of correlative contacts based on the scoring; presenting the initial set of correlative contacts along with a plurality of selectable communication recourses for each of the initial set of correlative contacts; initiating a communication with at least one of the initial set of correlative contacts upon selection of a corresponding communication recourse from the plurality of selectable communication recourses; and providing a plurality of selectable recourses to contact the target user based on the communication with the at least one of the initial set of correlative contacts. determining a plurality of correlative contacts between the source user and the target user from one or more communication platforms connecting the source user and the target user, wherein a correlative contact is a mutual contact of both the source user and the target user; scoring the plurality of correlative contacts based on one or more proximity parameters among the source user, each of the plurality of correlative contacts, and the target user, wherein the proximity parameters include information describing a level of acquaintance and/or geographical coincidence of the source user, target user and/or correlative contacts, and wherein scoring comprises assigning a primary weight to each of the one or more proximity parameters using a machine learning algorithm and computing a weighted average of the one or more proximity parameters for each of the plurality of correlative contacts; generating an initial set of correlative contacts from the plurality of correlative contacts based on the scoring; presenting the initial set of correlative contacts along with a plurality of selectable communication recourses for each of the initial set of correlative contacts; initiating a communication with at least one of the initial set of correlative contacts upon selection of a corresponding communication recourse from the plurality of selectable communication recourses; and providing a plurality of selectable recourses to contact the target user based on the communication with the at least one of the initial set of correlative contacts.