ECNU at SemEval-2017 Task 5: An Ensemble of Regression Algorithms with Effective Features for Fine-Grained Sentiment Analysis in Financial Domain
Mengxiao Jiang, Man Lan, Yuanbin Wu · 2017
This paper describes our systems submitted to the Fine-Grained Sentiment Analysis on Financial Microblogs and News task (i.e., Task 5) in SemEval-2017.This task includes two subtasks in microblogs and news headline domain respectively.To settle this problem, we extract four types of effective features, including linguistic features, sentiment lexicon features, domain-specific features and word embedding features.Then we employ these features to construct models by using ensemble regression algorithms.Our submissions rank 1st and rank 5th in subtask 1 and subtask 2 respectively.