Actualization of linguistic markers in political Internet discourse, and its peculiarities in the context of artificial neural network operation, and hate speech detection

Abstract

The article argues that the actualization of linguistic markers (lexical, grammatical, pragmatic, semantic) in the texts of political Internet discourse is crucial for understanding the context (social, emotional, modal, etc.) in them. It is emphasized that the use of innovative tools (in particular, artificial neural networks) is in line with the trends towards the integration of the mathematical paradigm into the humanities, which is manifested in the latter’s tendency to the humanities digital sciences, affective computing, etc. It is noted that the use of the outlined innovative tools creates the need to take into account an integrated approach to such research, which is manifested in the integration of the methodology of other (primarily related) sciences, which, in turn, will allow to take into account contextual determination, cultural features (gaps, realities, etc.), as well as to use the full potential of artificial neural networks in modern linguistic research. The author emphasizes the need to further develop the originality of the use of the latter in such studies: developing datasets, building a training algorithm, testing and retraining (if necessary), as well as integrating different layers into their structures and optimizing such a structure specifically for linguistic research (which combinations are productive and why, for what purpose, etc.) The author emphasizes the originality of the use of innovative tools (deep learning, machine learning, artificial neural networks) to deal with hate speech, misinformation, disinformation, and propaganda, which can take the form of sarcasm, irony, and absurdity in political Internet discourse, which requires further research and development of a new methodology to accurately identify such data and produce an inclusive and safe Internet environment.