This paper aims to understand complex social events that arise when communicating general concepts in the digital space. Today, we get informed through many different channels, at different times of the day, in different contexts, and on many different devices. In addition to that, more complexity is added by the bidirectional nature of the communication itself. People today react very quickly to specific topics through various means such as rating, sharing, commenting, tagging, icons, tweeting, etc. Such activities generate additional metadata to the information itself which become part of the original message. When planning proper communication we should consider all this. In such a complicated environment, the likelihood of a message's real meaning being received in a distorted or confused way is very high. However, as we have seen recently during the Covid-19 pandemic, at times, there is the need to communicate something, somewhat complicated in nature, while we need to make sure citizens fully understand the actual terms and meaning of the communication. This was the case faced by many governments worldwide when informing their population on the rules of conduct during the various lockdown periods. We analyzed trends and structure of social network data generated as a reaction to those official communications in Italy. Our goal is to derive a model to estimate whether the communication intended by the government was properly understood by the large population. We discovered some regularities in social media generated data related to "poorly" communicated issues. We believe it is possible to derive a model to measure how well the recipients grasp a specific topic. And this can be used to trigger real-time alerts when the need for clarification arises.