Abstract: A computer-implemented method for determining a relevance or rating score of a particular user in an electronic social network includes obtaining a digital representation of a local connection structure of the particular user in the network in a computer-readable non-volatile memory; determining a numerical value characteristic of the particular user's relevance; and outputting the numerical value. The numerical value is determined based on the connection structure of the particular user, and on degrees of all sets of users in the social network reachable from the particular user using at most k connections, where k is a fixed preset positive integer number, and based on a degree determined for each enumerated set, and where the degree of a set is determined as a number of connections connecting users inside the set to users outside.

Abstract: Embodiments of the present disclosure are directed towards a system and method for determining credibility and reliability of social media content. Embodiments may include receiving social media content from one or more social media applications, wherein the social media content includes a story, a source, and spread information. Embodiments may further include receiving a plurality of trusted global media inputs and analyzing, one or more of the social media content or the plurality of trusted global media inputs using machine learning. Embodiments may also include determining a score for one or more of the story, source, and spread information and generating a final score for the social media content based on the score.

Abstract: A computer-implemented method for determining a relevance or rating score of a particular user in an electronic social network includes obtaining a digital representation of a local connection structure of the particular user in the network in a computer-readable non-volatile memory; determining a numerical value characteristic of the particular user's relevance; and outputting the numerical value. The numerical value is determined based on the connection structure of the particular user, and on degrees of all sets of users in the social network reachable from the particular user using at most k connections, where k is a fixed preset positive integer number, and based on a degree determined for each enumerated set, and where the degree of a set is determined as a number of connections connecting users inside the set to users outside.

Abstract: A computer-implemented method for determining a relevance of a node in a network. A digital representation of a local neighborhood structure of the node in the network is obtained in a computer-readable non-volatile memory. A numerical value characteristic of the node's relevance is determined, and output to a user. The numerical value is determined based on the neighborhood structure of the node.

Abstract: A computer-implemented method for determining a relevance of a node in a network. A digital representation of a local neighborhood structure of the node in the network is obtained in a computer-readable non-volatile memory. A numerical value characteristic of the node's relevance is determined, and output to a user. The numerical value is determined based on the neighborhood structure of the node.