Systems and methods for social influence based loyalty and customer experience management in mobile communication networks

A system for determining an influence score for a first user of a plurality of users of a network, said system implemented in a social network analyzer comprising a processor coupled with a memory, the memory storing instructions executable by the processor to:

• create, by a discovery engine of the social network analyzer, a usage interaction graph based on mobile service usage data generated by interactions of the plurality of users in a mobile communication network, vertices of the social usage interaction graph representing the plurality of users and edge weights of the usage interaction graph being based on a plurality of weight parameters of at least one analytical model;
• determine, by the discovery engine, download of an Over-The-Top (OTT) application by the first user at a first time instance;
• upon determination of the download of the OTT application by the first user, initially detect, by the discovery engine, at a second time instance, co-location of a second user of the plurality of users with the first user within a first defined time frame from the first time instance, and subsequently detect, at a third time instance, relative to the co-location of the second user with the first user, download of the OTT application by the second user within a second defined time frame from the second time instance;
• determine, by the discovery engine, an edge weight between the first user and the second user in the interaction graph based on the detection of the co-location within the first defined time frame and the detection of the download of the OTT application by the second user within the second defined time frame, wherein said edge weight is determined further based on a combination of time and duration of interactions between the first user and the second user, nature and frequency of interactions between the first user and the second user, degree of overlap in OTT applications used by the first user and the second user, and number of times the first user and the second user are co-located, and wherein the edge weight is determined using weighted combinations of key performance indicators (KPIs) derived from the usage data;
• and
• derive and update, by a scoring engine of the social network analyzer, simultaneous to changes in the usage interaction graph and said edge weight, the influence score for the first user in the usage interaction graph based on the download of the OTT application by the second user within said second defined time frame from the second time instance.