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 content as well as the classification of event types (e.g. sports events, concerts, etc.). In this paper, we provide an extensive study of textual, visual, as well as multimodal representations for social event classification. We investigate strengths and weaknesses of the modalities and study 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.
This paper describes our participation in Social Detection Task@ MediaEval 2013, which involves the detection of social events with associated images in collaboratively annotated by online users. Two tasks are pursued: (i) cluster all images into events in a way that they belong together; (ii) classify the images based on event type. For this we have developed a framework for semantically structuring the social image collection. For Task 1 and Task2, we achieved an overall F1 main score 0.1426 and 0.4409 respectively.