We share almost all segments of our lives on the web, including our to-do's, meetings, events related to work or leisure. Not only we share with the world where we are going to be, but also how we are feeling in a given situation and with whom we are attending a certain event. If we ignore the individual aspect and look at a city as a whole, the people, who work and enjoy their free time in the city produce a sensor network. This network is continuously reporting about the current status of the city, in some cases even about its near future. These pieces of information are scattered on social media platforms, but most importantly, they pile up in an unprocessed manner. By collecting this information about a city and especially, about its traffic as a unit, we can expect a relatively accurate picture. If we complement this with data from other sources — such as weather forecast data, which can significantly influence our activities — we can estimate the tendency of urban citizens' movement, predict which traffic junctions can become overladen. In our article, we use the data from latest time period to prove our concept.