Multimodal Classification of Events in Social Media
This addresses the challenge of accurately categorizing event-related content on platforms like Flickr and Instagram, which is incremental as it builds on existing methods with multimodal integration.
The paper tackled the problem of classifying social events in social media content by studying textual, visual, and multimodal representations, resulting in a multimodal approach that outperformed state-of-the-art methods and set a new baseline.
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.