How to predict citizen engagement in urban innovation projects?

Blogpost by Julien Carbonnell: “Citizen engagement in decision-making has proven to be a key factor for success in a smart city project and a must-have of contemporary democratic regimes. While inhabitants are all daily internet users, they widely inform themselves about their political electives’ achievements during the mandate, interact with each other on social networks, and by word-of-mouth on messaging apps or phone calls to form an opinion.

Unfortunately, most of the smart cities’ rankings lack resources to evaluate the citizen engagement dynamic around the urban innovations deployed. Indeed this data can’t be found on official open data portals, focused instead on cities’ infrastructure and quality of life. These include the number of metro stations, the length of bike lanes, air pollution, and tap water quality. Some of them also include field investigation such as the amount of investment in this or that urban area and communication dynamics about a new smart city project.

If this kind of formal information provides a good overview of the official state of development of a city, it does not give any insight from the inhabitants themselves and sounds out the street vibes of a city.

So, I’ve been working on filling this gap for the last 3 years and share in Democracy Studio all the elements of my method and tools built for conducting such analysis. To do so, I have notably been collecting inhabitants’ participation in a survey study in three case study cities: Taipei (Taiwan), Tel Aviv (Israel), and Tallinn (Estonia). I collected 366 answers by contacting inhabitants randomly online (Facebook groups, direct messages on LinkedIn, and through messaging apps) and in-person, in events related to my field of interest (Smart-City and Urban Innovation Startups). The resulting variables have been integrated into machine learning models, which finally performed a very satisfying prediction of the citizen engagement in my case studies….(More)”.