Speech Perception in Digital Content: Network Conflicts in City Projects

Abstract

The article presents the results of the analysis on perception by network actors implementation of urban projects that affect the environment. An algorithm for adapting linguistic, psycholinguistic and sociolinguistic methods for interpreting Big Data in real time is proposed. The study has enabled identifying several conflict situation markers and rating social tension compilation. The transdisciplinary approach has been applied with the use of neural network technologies, text analysis, analysis of word associations, content analysis, sentiment analysis. The material for the study was the data of social networks, microblogs, blogs, instant messengers, video hosting, video materials, forums and reviews on the construction of metro stations in Moscow. Analysis of the data showed the ambivalent attitude of Muscovites to the construction of new metro facilities. A positive reaction, due to the need to develop the transport structure of the city, improve the transport situation, is confronted with the protest of residents who put forward a number of claims. Verbal data examination has made it possible to reveal the rating of social tension around new metro facilities. The selection and analysis of the semantic and associative network with the use of neural network technologies contributed to clarifying and expanding the linguistic paradigm in speech perception of digital content. The results of the study can be used in both text and network analysis.