News Popularity Prediction Using Topic Modelling

2021

Closed access Metadata (CSL-JSON)
DOI 10.1109/sist50301.2021.9465884
Data confidence 70 medium
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Abstract

The tasks of Natural Language Processing (hereinafter - NLP) are very topical today, in particular in the context of the application of machine learning and artificial intelligence models. In this work the approach allowing to carry out classification of texts with the minimal required manual markup is considered. The problem of prediction of resonance of news in the Kazakhstani media space where resonance is understood as abnormal interest of the public to the publication within the limits of a concrete information source is considered. The proposed model is implemented and tested within an informational system.