Practical OSINT investigation in Twitter utilizing AI-based aggressiveness analysis

Open-source intelligence is gaining popularity due to the rapid development of social networks. There is more and more information in the public domain. One of the most popular social networks is Twitter. 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, as this information can be important not only for the owner of the channel in the social network, but also for other studies that in some way influence user accounts and their behavior in the social network. Furthermore, this work includes a detailed analysis and evaluation of the Tweety library capabilities and situations in which it can be effectively applied. Lastly, this work includes the creation and description of a compiled neural network whose purpose is to predict changes in the number of likes, reposts, quotes, and retweets from the aggressiveness of the post text for a separate profile.