The article is devoted to describing approaches to analyzing the information space using low-code platforms in order to identify factors that form new identities of Azerbaijan and the unique features of the country’s information landscape. The article describes the steps to identify key themes and collect big data in the form of text corpora from various Internet sources and analyze the data. In terms of data analysis, the study of the sentiment of the text and the identification of opinion leaders is carried out; the article also includes monitoring of key topics, visualized for a visual presentation of the results.

Keywords: data analytics, trend monitoring, sentiment analysis, data visualization, low-code, Kribrum, Polyanalyst, big data

This article discusses the aspects of collecting and processing textual data from social media and mass media in the context of assessing the social sentiments of the population of certain macro-regions. Text data is an important source of reflecting the sentiments of society and can be collected, pre-processed and analyzed using modern technical tools, considering the specifics of the hypotheses under study and the tasks set. This context is an important part of the system of comprehensive security of macro-regions in their cultural, social, economic, political aspects. The discussed approaches include the collection of relevant data, their processing and analysis using data mining tools.

Keywords: text analysis, media data, natural language processing, social sentiment assessment, data analysis