Social media represent an unprecedented source of information about every topic of our daily lives. Since music plays a vital role for almost everyone, information about music items and artists is found in abundance in user-generated data. In this talk, I will report on our recent research on using social media sources to extract music-related information, aiming to improve music retrieval and recommendation. More precisely, I will elaborate on the following questions: i) Which factors are important to human perception of music? ii) How to extract music listening events from social media, in particular microblogs? iii) How to mine and annotate listening patterns from this data? iv) What can this kind of data tell us about the music taste of people around the world? v) Can we make accessible music listening data mined from social media in an intuitive way?
Markus Schedl graduated in Computer Science from the Vienna University of Technology. He earned his Ph.D. in Computational Perception from the Johannes Kepler University Linz, where he is employed as Assistant Professor at the Department of Computationa Perception. He further studied International Business Administration at the Vienna University of Economics and Business Administration as well as at the Handelshögskolan of the University of Gothenburg, which led to a Master's degree. Markus (co-)authored more than 70 refereed conference papers and journal articles.
Furthermore, he serves on various program committees and reviewed submissions to several conferences and journals. His main research interests include web and social media mining, information retrieval, multimedia, music information research, and user interfaces. Since 2007, Markus has been giving several lectures, for instance, "Music Information Retrieval", "Exploratory Data Analysis", "Multimedia Search and Retrieval" and "Learning from User-generated Data", the latter two being in preparation. He further spent several guest lecturing stays at the Universitat Pompeu Fabra, Barcelona, Spain, the Utrecht University, the Netherlands, the Queen Mary, University of London, UK, and the Kungliga Tekniska Högskolan, Stockholm, Sweden.