@article{zeppelzauer_multimodal_2016, title = {Multimodal classification of events in social media}, issn = {0262-8856}, url = {https://arxiv.org/pdf/1601.00599}, doi = {10/ghpp2q}, abstract = {Abstract A large amount of social media hosted on platforms like Flickr and Instagram is related to social events. The task of social event classification refers to the distinction of event and non-event-related contents as well as the classification of event types (e.g. sports events and concerts). In this paper, we provide an extensive study of textual, visual, as well as multimodal representations for social event classification. We investigate the strengths and weaknesses of the modalities and study the synergy effects between the modalities. Experimental results obtained with our multimodal representation outperform state-of-the-art methods and provide a new baseline for future research.}, journal = {Image and Vision Computing}, author = {Zeppelzauer, Matthias and Schopfhauser, Daniel}, year = {2016}, keywords = {2016, Center for Artificial Intelligence, Computer Vision, Department Medien und Digitale Technologien, Department Technologie, FH SP Data Analytics \& Visual Computing, Forschungsgruppe Media Computing, Institut für Creative Media Technologies, Machine Learning, Media Computing Group, Multimodal retrieval, Publikationstyp Schriftpublikation, Wiss. Beitrag, best, best-mzeppelzauer, peer-reviewed}, }