User Attitudes towards Machine-Learning-Generated Content as the Factor Influencing Consumer Engagement

The topic of creating texts using special algorithms is gaining more and more popularity in the modern world in the context of the dynamic development of computer technology. At the same time, within the framework of social networks, the ability to artificially generated content is becoming more and more relevant. This is due to the fact that the introduction of technologies improves the process of maintaining a brand account and significantly saves the time of an SMM specialist - he will only be required to edit the text and select an accompanying illustration. However, there is an obvious gap in the scientific literature in understanding how the knowledge that content is artificially created affects the level of consumer engagement. Thus, the problem of this study is following: the impact of knowledge about the artificial origin of content on user engagement. Purpose of the study is following: to identify the presence and nature of the relationship between consumer behavior in a social network and the perception of artificially created content. The study uses two methods, the first of which is based on writing code (in the Python programming language) to generate posts on a social network. The second research method involves conducting an experimental survey that will reveal how the knowledge that content is created artificially affects the level of consumer engagement and his attitude to that content.