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Subjectivity is the expression of internal opinions or beliefs which cannot be objectively observed or verified, and has been shown to be important for sentiment analysis and word-sense disambiguation.
Review conversational reading comprehension
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Long Short-Term Memory
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Development and use of a gold-standard data set for subjectivity classifications
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Project Magellan: Collecting cross-cultural affective meanings via the internet
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A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts
Bo Pang and Lillian Lee. 2004 · 2004
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Annotating Expressions of Opinions and Emotions in Language
Janyce Wiebe, Theresa Wilson, and Claire Cardie. 2005 · 2005
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Word sense and subjectivity
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Building a sentiment summarizer for local service reviews
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Subjectivity word sense disambiguation
Cem Akkaya, Janyce Wiebe, and Rada Mihalcea. 2009 · 2009
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Multilingual subjectivity: Are more languages better?
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Latent aspect rating analysis on review text data: a rating regression approach
Hongning Wang, Yue Lu, and Chengxiang Zhai. 2010 · 2010
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Answering Opinion Questions on Products by Exploiting Hierarchical Organization of Consumer Reviews
Jianxing Yu, Zheng-Jun Zha, and Tat-Seng Chua. 2012 · 2012
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Samaneh Abbasi Moghaddam. 2013 · 2013
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Relation Extraction with Matrix Factorization and Universal Schemas
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Dirk Weissenborn, Georg Wiese, and Laura Seiffe. 2017 · 2017
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Parameter sharing between dependency parsers for related languages
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Language Models are Unsupervised Multitask Learners
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Sebastian Riedel, Limin Yao, Andrew McCallum, and Benjamin M. Marlin. 2013 · 2013
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Addressing Complex and Subjective Product-Related Queries with Customer Reviews
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Aspect extraction for opinion mining with a deep convolutional neural network
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Jack the Reader - A Machine Reading Framework
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Mansi Gupta, Nitish Kulkarni, Raghuveer Chanda, Anirudha Rayasam, and Zachary C. Lipton. 2019 · 2019
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Subjective Databases
Yuliang Li, Aaron Feng, Jinfeng Li, Saran Mumick, Alon Y. Halevy, Vivian Li, and Wang-Chiew Tan. 2019 · 2019
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CoQA: A Conversational Question Answering Challenge
Siva Reddy, Danqi Chen, and Christopher D. Manning. 2019 · 2019
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Latent Multi-task Architecture Learning
Sebastian Ruder, Joachim Bingel, Isabelle Augenstein, and Anders Søgaard. 2019 · 2019
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Sampo: Unsupervised Knowledge Base Construction for Opinions and Implications
Nikita Bhutani, Aaron Traylor, Chen Chen, Xiaolan Wang, Behzad Golshan, and Wang-Chiew Tan. 2020 · 2020
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Unsupervised Evaluation for Question Answering with Transformers
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