New Governance Path through Digital Platforms and the Old Urban Planning Process in Italy

Current acceleration in digital practices, unexpected challenges in our social and spatial interactions, and sudden limitations in our physical spaces, mark unpredictable changes in our old normal. A different normal—as generated nowadays from the global pandemic 2020—is setting out, indeed, a mixed physical/virtual framework of the modification humanity is undertaking in being pushed into a new “digital age”; or better, as many scholars are saying, into the New Normal. A new normal in which the balance between physical and virtual interactions became in vantage of the second one in just one year, by increasing, at the same time, both the quantity and the quality of exchanging digital data. It is drafted a bi-dimensional enlarging that re-calls and stresses moreover the value of certain qualitative multi-data-based analyses aimed in reading the people’s common-sense to extrapolate wishes and needs within their daily lives; as the sentiment analysis applied to the urban planning processes wants to do. In synthesis, the bigger number of qualitative data coming from the web (from Socials mainly) became more affordable and more reliable (due to the new larger number of digital flows) in shaping new ways for a more effective public participation within the conventional planning process. In the pages of this article authors, through different but shared viewpoints, propose a possible answer to the topic of a new “Governance 3.0” addressing the attempt of a change of those consolidated paradigms within which the spatial dimension—in which we live and we act day by day—is shaped through planning processes consolidate over the years. Analyzing the relationship between Technocracy and Democracy, as defined by Khanna, it is argued that it is possible to realize new forecasts and to acquire a more democratic and participatory (inclusive) dimension of Governance, thanks to new digital technologies by exploring the general unconscious “feeling” of people, through anonymous data collection from Socials and similar platforms and without any direct or indirect interference with it. The Sentiment Analysis can “define automatic tools able to extract subjective information from texts in natural languages, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision-support system or a decision-maker.