Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area. We present a computer-assisted literature review, where we utilize both text mining and qualitative coding, and analyze 6,996 papers from ...
Sentiment analysis comes under the umbrella of Natural Language Processing, click here to read about the best and free resources to get started with NLP. Sentiment analysis is like a gateway to AI based text analysis. For any company or data scientist looking to extract meaning out of an ...
49. Context-aware Embedding for Targeted Aspect-based Sentiment Analysis会议:ACL 2019.作者:Bin Liang, Jiachen Du, Ruifeng Xu, Binyang Li, Hejiao Huang链接:aclweb.org/anthology/P150. Attention and Lexicon Regularized LSTM for Aspect-based Sentiment Analysis会议:ACL 2019. Student Research Workshop...
Sentiment analysis is one of the fastest growing research areas in computer science, making it challenging to keep track of all the activities in the area. We present a computer-assisted literature review, where we utilize both text mining and qualitative coding, and analyze 6996 papers from Scop...
Duyu Tang, Furu Wei, Bing Qin, Nan Yang, Ting Liu, Ming Zhou. 2016. Sentiment Embeddings with Applications to Sentiment Analysis. IEEE Transactions on Knowledge and Data Engineering (TKDE). [https://www.mendeley.com/research-papers/sentiment-embeddings-applications-sentiment-analysis/] ...
Other text sources:Sentiment analysis is possible on any text-based data. This includes electronic health reports such as healthcare data and research papers; public information, as in government websites and platforms and even gaming sites like Twitch. ...
Our Web of Science Sentiment Analysis Articles Model and Map of the World demonstrates that nations with an unfavorable macroenvironment published disproportionately fewer papers on sentiment analysis. This research benefits stakeholders by providing comprehensive and holistic information and data analysis, ...
Seminal papers on developing ML techniques for sentiment analysis include Pang et al. (2002) and Pang and Lee (2005). 使用结构化机器学习训练预测模型的能力,而不是依赖简单的词库,是 ML 方法相对于词法方法的一个重要潜在优势。ML 方法可以利用线性分类器以及越来越多的深度学习架构来自动学习单词和整个...
Some subcategories of research in sentiment analysis include: multimodal sentiment analysis, aspect-based sentiment analysis, fine-grained opinion analysis, language specific sentiment analysis. More recently, deep learning techniques, such as RoBERTa and T5, are used to train high-performing sentiment ...
Bridging the Gap for Test-Time Multimodal Sentiment Analysis Multimodal sentiment analysis (MSA) is an emerging research topic that aims to understand and recognize human sentiment or emotions through multiple modalities. However, in real-world dynamic scenarios, the distribution of target data is ...