Practical OSINT investigation in Twitter utilizing AI-based aggressiveness analysis

Open-source intelligence is gaining popularity these days due to the development of social networks. There is more and more information in the public domain. Twitter is one of the most popular social networks, so it’s worth analyzing its information. It was chosen to analyze the dependence of changes in the number of likes, reposts, quotes, and retweets on the aggressiveness of the post text for a separate profile since this information may be important not only for the owner of the channel on the social network but also for other studies that somehow affect user accounts and their behavior on the social network. also, the task of this work was a detailed analysis and evaluation of the capabilities of the tweety library and situations in which it can be effectively applied. also, the creation and description of a compiled neural network, the purpose of which is to predict changes in the number of likes, re-posts, quotes, and retweets from the aggressiveness of the post text for a separate profile.