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Development of an algorithm for fixing the citizens' assessments of digital transformation processes based on text analysis

The paper presents an approach to the detection of social well-being traits through news analysis on topic of digital transformation. The paper describes the key stages of developing methodology for automatic work with texts about the digital transformation of society, based on the machine learning methods and mathematic approaches like Transformers and MCDM. The authors reveal the process of data preprocessing and transformation, describe the characteristics of the news dataset used for training and validating machine learning models and the social media dataset used for evaluating the proposed algorithm, the entity and topic labeling process, the implementation of sentiment analysis and text classification tasks. The paper presents the obtained results and models' metrics: for the text classification task the model gave the result between 76-79% of F1-score, for the sentiment analysis task - 71% of F1-score. The plan of further steps towards developing models of detecting citizens’ assessment of government e-services efficiency is gained.