1 Hit in 2.8 sec

THU_NGN at SemEval-2018 Task 1: Fine-grained Tweet Sentiment Intensity Analysis with Attention CNN-LSTM

Chuhan Wu, Fangzhao Wu, Junxin Liu, Zhigang Yuan, Sixing Wu, Yongfeng Huang
2018 Proceedings of The 12th International Workshop on Semantic Evaluation  
Therefore, the SemEval-2018 Task 1 is aimed to automatically determine the intensity of emotions or sentiment of tweets to mine fine-grained sentiment information.  ...  In order to address this task, we propose a system based on an attention CNN-LSTM model. In our model, LSTM is used to extract the long-term contextual information from texts.  ...  Conclusion Identifying the intensity of emotions or sentiment is important for fine-grained sentiment analysis. Thus, the Semeval-2018 task 1 is aimed to analyze the affective intensity of tweets.  ... 
doi:10.18653/v1/s18-1028 dblp:conf/semeval/WuWLYWH18 fatcat:nkcingorrratpegxispjmbb5rq