.png){kind=icon}
返回
Implicit sentiment analysis based on multi-feature neural network model
.png){kind=icon}
PRE
AI
DOI：10.1007/s00500-021-06486-7.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
As social media has become a ubiquitous part of daily life, researchers made a great progress in identifying the emotion in user-generated texts. However, it is a challenging task as people express their emotion in explicit and implicit ways. This paper focuses on the problem of identifying sentiments from implicit sentences which contain no emotional word or phrase. Most of the existing sentiment classification models cannot identify the sentiments accurately since they usually focus on extracting features from grammatical information without taking contextual information into account. In this paper, we argue that the contextual information is the key to identify sentiments in implicit sentences. Moreover, multiple features extracting from different aspects should be taken into account to improve sentiment identification. This paper proposes a multi-feature neural network model considering three aspects: contextual information, syntactic information and semantic information. To better get the semantic information of the sentence, we propose an attention mechanism based on contextual affective space. The experimental results on the SMP2019-ECISA dataset demonstrate that our model outperforms the previous systems and strong neural baselines.
Keyword:
Implicit sentiment analysis
Multi-feature
Contextual information
Syntactic information
Semantic information
Contextual affective space
期刊
IF:
2.5
论文数:
1.0W
被引数:
2.1W
机构
引用论文
Cobalt and Copper Composite Oxides as Efficient Catalysts for Preferential Oxidation of CO in H2-Rich Stream钴和铜复合氧化物作为H2-Rich流中CO优先氧化的有效催化剂
PREAI
分享收藏Identification of fact-implied implicit sentiment based on multi-level semantic fused representation
PREAI
分享收藏Identifying Implicit Polarity of Events by Using an Attention-Based Neural Network Model.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏Context-Specific Heterogeneous Graph Convolutional Network for Implicit Sentiment AnalysisIEEE ACCESSOAAI
IEEE ACCESSIF3.6
OAAI分享收藏BiLSTM with Multi-Polarity Orthogonal Attention for Implicit Sentiment AnalysisNEUROCOMPUTING
NEUROCOMPUTINGIF6.5
PREAI
分享收藏The entanglement of two moving atoms interacting with a single-mode field via a three-photon process
PREAI
分享收藏
查看更多内容