# Seernet at EmoInt-2017: Tweet Emotion Intensity Estimator

arXiv: https://arxiv.org/abs/1708.06185 · HTML: https://mlsanity.com/paper/1708.06185/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Aug 2017.

## Built on by (most cited first, 2 of 2)

- ["splink" is happy and "phrouth" is scary: Emotion Intensity Analysis for Nonsense Words](https://mlsanity.com/paper/2202.12132/) (2022)
- [Identifying negativity factors from social media text corpus using sentiment analysis method](https://mlsanity.com/paper/2107.02175/) (2021)

## Abstract (arXiv)

The paper describes experiments on estimating emotion intensity in tweets using a generalized regressor system. The system combines lexical, syntactic and pre-trained word embedding features, trains them on general regressors and finally combines the best performing models to create an ensemble. The proposed system stood 3rd out of 22 systems in the leaderboard of WASSA-2017 Shared Task on Emotion Intensity.