Social-IQ Dataset

May 17, 2019

As intelligent systems increasingly blend into our everyday life, artificial social intelligence becomes a prominent area of research. Human language offers a unique unconstrained approach to probe through questions and reason through answers about social situations. This unconstrained approach extends previous attempts to model social intelligence through numeric supervision (e.g. sentiment and emotions labels). Social-IQ brings novel challenges to the field of artificial intelligence which sparks future research in social intelligence modeling, visual reasoning, and multimodal question answering.


February 10, 2018

CMU Multimodal Opinion Sentiment and Emotion Intensity (CMU-MOSEI) is the largest dataset of sentence level sentiment analysis and emotion recognition in online videos. CMU-MOSEI contains more than 65 hours of annotated video from more than 1000 speakers and 250 topics. The dataset was introduced in the 2018 Association for Computational Linguistics 2018 and used in the co-located First Grand Challenge and Workshop on Human Multimodal Language. 

CMU-MOSI Dataset

January 04, 2017

CMU Multimodal Opinion Sentiment Intensity (CMU-MOSI) is a dataset of opinion level sentiment intensity in online videos. CMU-MOSI opened door to utterance level sentiment analysis in English videos. The dataset was largest of it's kind at release time. It contains 2199 opinion utterances with sentiment annotated between very negative to very positive in seven Likert steps. 

Trafficking-10K dataset

March 01, 2017

Human trafficking is a global epidemic affecting millions of people across the planet. Sex trafficking, the dominant form of human trafficking, has seen a significant rise mostly due to the abundance of escort websites, where human traffickers can openly advertise among at-will escort advertisements. For the first time in scientific history, we present a novel dataset called Trafficking-10k, with more than 10,000 advertisements annotated for this task. The dataset contains two sources of information per advertisement: text and images. 

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