Identification of information tonality based on Bayesian approach and neural networks

TL;DR

This paper presents a Bayesian and neural network-based model for identifying the positive or negative tone of information, leveraging statistical regularities in lexemes, with a focus on simplicity and versatility.

Contribution

It introduces a novel, simple, and versatile method for tonality detection using Bayesian approach combined with neural networks, applicable to various texts.

Findings

Effective in detecting information tone based on lexemes

Applicable to controlling spam and analyzing text sentiment

Demonstrates high simplicity and versatility

Abstract

A model of the identification of information tonality, based on Bayesian approach and neural networks was described. In the context of this paper tonality means positive or negative tone of both the whole information and its parts which are related to particular concepts. The method, its application is presented in the paper, is based on statistic regularities connected with the presence of definite lexemes in the texts. A distinctive feature of the method is its simplicity and versatility. At present ideologically similar approaches are widely used to control spam.