Thanks to the advances in Web development, internet usage is not limited to the static web browsing any more these days. With the bloom of social media, it is time to make good use of the freely accessible user-generated content to unmask new information. In recent years, many researchers have actually focused on user-contributed data in their studies. Very few of them have; however, investigated the trajectory patterns in contexts other than the spatiotemporal information. The work presented in this thesis explores the possibility of mining the trajectory patterns in the context of the Flickr user groups (according to "location", i.e., main residence) and seasons (summer versus winter). Studying the trajectory patterns in these contexts is novel. To attain this overall goal, the three largest Flickr user groups, who have visited the city of Vienna, Austria in a period of about 5 years (2007-2011), were selected. Then, the 10 most visited landmarks were sorted out for each group in each season. In the end, the trajectory patterns of each group visiting these top landmarks in each season were analysed. Although the landmarks and trajectory patterns of each group were overall similar, some interesting differences could be uncovered by considering the two contexts of user groups and seasons together.