Neural Network Models and Cognitive Computing from Social Media Data: Perception of Situation

Abstract

The paper presents the development of various types of models using cognitive computing based on speech data of social media actors to reveal the presence/absence of social tension in the areas where urban development projects are being implemented, as illustrated by the construction of the Nizhegorodskaya transport interchange hub in Moscow (Russia). The empirical base of the study was data from social networks, microblogs, blogs, instant messengers, video hosting sites, forums, Internet media, subject-related portals and reviews on the project implementation. The research was carried out using a transdisciplinary approach, including semantic analysis, neural network technologies and mathematical modeling methods. The study showed the consistency of the results obtained during the application of various types of models. Semantic analysis of content using neural network technologies showed a neutral perception of the project by residents, the absence of social stress in the construction areas. The results of the analysis performed with autoregressive models confirmed the results obtained.