# EmotionGIF-IITP-AINLPML: Ensemble-based Automated Deep Neural System for predicting category(ies) of a GIF response

arXiv: https://arxiv.org/abs/2012.12756 · HTML: https://mlsanity.com/paper/2012.12756/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Dec 2020.

## Built on by (most cited first, 1 of 1)

- [SocialNLP EmotionGIF 2020 Challenge Overview: Predicting Reaction GIF Categories on Social Media](https://mlsanity.com/paper/2102.12073/) (2021)

## Abstract (arXiv)

In this paper, we describe the systems submitted by our IITP-AINLPML team in the shared task of SocialNLP 2020, EmotionGIF 2020, on predicting the category(ies) of a GIF response for a given unlabelled tweet. For the round 1 phase of the task, we propose an attention-based Bi-directional GRU network trained on both the tweet (text) and their replies (text wherever available) and the given category(ies) for its GIF response. In the round 2 phase, we build several deep neural-based classifiers for the task and report the final predictions through a majority voting based ensemble technique. Our proposed models attain the best Mean Recall (MR) scores of 52.92% and 53.80% in round 1 and round 2, respectively.