International Journal of Geo-Information Article Geo-Tagged Social Media Data-Based Analytical Approach for Perceiving Impacts of Social Events Ruoxin Zhu 1,* , Diao Lin 1 , Michael Jendryke 2,3 , Chenyu Zuo 1, Linfang Ding 1,4 and Liqiu Meng 1 1 Chair of Cartography, Technical University of Munich, 80333 Munich, Germany;
[email protected] (D.L.);
[email protected] (C.Z.);
[email protected] (L.D.);
[email protected] (L.M.) 2 State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
[email protected] 3 School of Resources and Environmental Science, Wuhan University, Wuhan 430079, China 4 KRDB Research Centre, Faculty of Computer Science, Free University of Bozen-Bolzano, 39100 Bolzano, Italy * Correspondence:
[email protected]; Tel.: +49-152-5723-5586 Received: 19 October 2018; Accepted: 20 December 2018; Published: 29 December 2018 Abstract: Studying the impact of social events is important for the sustainable development of society. Given the growing popularity of social media applications, social sensing networks with users acting as smart social sensors provide a unique channel for understanding social events. Current research on social events through geo-tagged social media is mainly focused on the extraction of information about when, where, and what happened, i.e., event detection. There is a trend towards the machine learning of more complex events from even larger input data. This research work will undoubtedly lead to a better understanding of big geo-data. In this study, however, we start from known or detected events, raising further questions on how they happened, how they affect people’s lives, and for how long.