Text Emotion Analysis of BGRU Model Based on the Fusion of Emoticons

EasyChair Preprint 3696

Abstract

Micro-blog is a platform for users to get information and convey their own ideas. In recent years, the emotional analysis of micro-blog has gradually become a hot topic. The publication of micro blog not only includes text, but also emoticons are a part that cannot be ignored. Traditional research methods ignore the importance of emoticons to the emotional polarity of text when preprocessing the micro blog. This paper proposes a research method of text emotion analysis based on the fusion of emoticons. By micro-blog to crawl the data preprocessing, selected text in the emoticons, using emotional dictionary gives corresponding weights and calculate the score, then transform text into the corresponding word vector sequence, using BGRU network context information text emotion tendency, finally selects the Conditional Random Field polarity judgment of text. The experimental results show that the new method is superior to the traditional method.

Keyphrases: BGRU, BLSTM, CNN, CRF, Emoticons, GRU, Sentiment Analysis, machine learning

@booklet{EasyChair:3696,
  author    = {Yong Li and Xiao-Jun Yang and Min Zuo and Rui-Jun Liu and Qing-Yu Jin},
  title     = {Text Emotion Analysis of BGRU Model Based on the Fusion of Emoticons},
  howpublished = {EasyChair Preprint 3696},
  year      = {EasyChair, 2020}}