ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models

2018-06-01SEMEVAL 2018Unverified0· sign in to hype

Huimin Xu, Man Lan, Yuanbin Wu

Unverified — Be the first to reproduce this paper.

Abstract

This paper describes our submissions to SemEval 2018 task 1. The task is affect intensity prediction in tweets, including five subtasks. We participated in all subtasks of English tweets. We extracted several traditional NLP, sentiment lexicon, emotion lexicon and domain specific features from tweets, adopted supervised machine learning algorithms to perform emotion intensity prediction.

Tasks

BIG-bench Machine Learning Emotion Classification Feature Engineering General Classification Prediction Sentiment Analysis

ECNU at SemEval-2018 Task 1: Emotion Intensity Prediction Using Effective Features and Machine Learning Models

Abstract

Tasks

Reproductions