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We present 3MASSIV, a multilingual, multimodal and multi-aspect,expertly-annotated dataset of diverse short videos extracted from short-videosocial media platform - Moj. 3MASSIV comprises of 50k short videos (20 secondsaverage duration) and 100K unlabeled videos in 11 different languages andcaptures popular short video trends like pranks, fails, romance, comedyexpressed via unique audio-visual formats like self-shot videos, reactionvideos, lip-synching, self-sung songs, etc. 3MASSIV presents an opportunity formultimodal and multilingual semantic understanding on these unique videos byannotating them for concepts, affective states, media types, and audiolanguage. We present a thorough analysis of 3MASSIV and highlight the varietyand unique aspects of our dataset compared to other contemporary populardatasets with strong baselines. We also show how the social media content in3MASSIV is dynamic and temporal in nature, which can be used for semanticunderstanding tasks and cross-lingual analysis.

3MASSIV: Multilingual, Multimodal and Multi-Aspect dataset of Social Media Short Videos