@inproceedings{duppada-etal-2018-seernet,
title = "{S}eer{N}et at {S}em{E}val-2018 Task 1: Domain Adaptation for Affect in Tweets",
author = "Duppada, Venkatesh and
Jain, Royal and
Hiray, Sushant",
booktitle = "Proceedings of the 12th International Workshop on Semantic Evaluation",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S18-1002",
doi = "10.18653/v1/S18-1002",
pages = "18--23",
abstract = "The paper describes the best performing system for the SemEval-2018 Affect in Tweets(English) sub-tasks. The system focuses on the ordinal classification and regression sub-tasks for valence and emotion. For ordinal classification valence is classified into 7 different classes ranging from -3 to 3 whereas emotion is classified into 4 different classes 0 to 3 separately for each emotion namely anger, fear, joy and sadness. The regression sub-tasks estimate the intensity of valence and each emotion. The system performs domain adaptation of 4 different models and creates an ensemble to give the final prediction. The proposed system achieved 1stposition out of 75 teams which participated in the fore-mentioned sub-tasks. We outperform the baseline model by margins ranging from 49.2{\%} to 76.4 {\%}, thus, pushing the state-of-the-art significantly.",
}
Markdown (Informal)
[SeerNet at SemEval-2018 Task 1: Domain Adaptation for Affect in Tweets](https://aclanthology.org/S18-1002) (Duppada et al., SemEval-*SEM 2018)
ACL