EICA at SemEval-2017 Task 4: A Simple Convolutional Neural Network for Topic-based Sentiment Classification

2017-08-01SEMEVAL 2017Unverified0· sign in to hype

Maoquan Wang, Shiyun Chen, Yufei Xie, Lu Zhao

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Abstract

This paper describes our approach for SemEval-2017 Task 4 - Sentiment Analysis in Twitter (SAT). Its five subtasks are divided into two categories: (1) sentiment classification, i.e., predicting topic-based tweet sentiment polarity, and (2) sentiment quantification, that is, estimating the sentiment distributions of a set of given tweets. We build a convolutional sentence classification system for the task of SAT. Official results show that the experimental results of our system are comparative.

Tasks

Classification Feature Engineering General Classification Sentence Sentence Classification Sentiment Analysis Sentiment Classification Twitter Sentiment Analysis

EICA at SemEval-2017 Task 4: A Simple Convolutional Neural Network for Topic-based Sentiment Classification

Abstract

Tasks

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