Social media actors: perception and optimization of influence across different types

Abstract

The paper deals with the analysis of the communicative behavior of various types of actors, speech perception and optimization of influence based on social media data and is an extended version of the report presented at CSoNet 2020 and published based on the deliverables of the conference. The paper proposes an improved methodology that is tested on the new material of conflicts regarding urban planning. The research was conducted on the material of social media concerning the construction of the South-East Chord in Moscow (Russia). The study involved a cross-disciplinary approach using neural network technologies, complex networks analysis. The dataset included social networks, microblogs, forums, blogs, videos, reviews. This paper presents the semantic model for the influence maximization analysis in social networks using neural network technologies, also proposed a variant of analyzing the situation with individual and collective actors, multiple opinion leaders, with a dynamic transformation of the hierarchy and ratings according to various parameters.