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Affect preferences vary with user demographics, and tapping into demographic information provides important cues about the users' language preferences.
Multi-task deep neural networks for natural language understanding
Xiaodong Liu, Pengcheng He, Weizhu Chen, and Jianfeng Gao. 2019 · 1901
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Glossbert: Bert for word sense disambiguation with gloss knowledge
Luyao Huang, Chi Sun, Xipeng Qiu, and Xuanjing Huang. 2019 · 1908
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Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 1908
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Learning word ratings for empathy and distress from document-level user responses
João Sedoc, Sven Buechel, Yehonathan Nachmany, Anneke Buffone, and Lyle Ungar. 2019 · 1912
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Note on the sampling error of the difference between correlated proportions or percentages
Quinn McNemar. 1947 · 1947
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“cloze procedure”: A new tool for measuring readability
Wilson L Taylor. 1953 · 1953
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The kent-rosanoff word association: Word association norms as a function of age
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Interpersonal reactivity index (iri)
Mark H Davis. 1980 · 1980
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Distress and empathy: Two qualitatively distinct vicarious emotions with different motivational consequences
C Daniel Batson, Jim Fultz, and Patricia A Schoenrade. 1987 · 1987
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Affective Computing
Rosalind W. Picard. 1997 · 1997
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Sympathy and empathy: Emotional responses to advertising dramas
Jennifer Edson Escalas and Barbara B Stern. 2003 · 2003
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Effects of age and gender on blogging
Jonathan Schler, Moshe Koppel, Shlomo Argamon, and James W Pennebaker. 2006 · 2006
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Modeling and evaluating empathy in embodied companion agents
Scott W McQuiggan and James C Lester. 2007 · 2007
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SemEval-2007 task 14: Affective text
Carlo Strapparava and Rada Mihalcea. 2007 · 2007
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Semi-supervised recursive autoencoders for predicting sentiment distributions
Richard Socher, Jeffrey Pennington, Eric H. Huang, Andrew Y. Ng, and Christopher D. Manning. 2011 · 2011
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“i help because i want to, not because you tell me to” empathy increases autonomously motivated helping
Louisa Pavey, Tobias Greitemeyer, and Paul Sparks. 2012 · 2012
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Analyzing the language of therapist empathy in motivational interview based psychotherapy
Bo Xiao, Dogan Can, Panayiotis G Georgiou, David Atkins, and Shrikanth S Narayanan. 2012 · 2012
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Language and gender
Penelope Eckert and Sally McConnell-Ginet. 2013 · 2013
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Min Lin, Qiang Chen, and Shuicheng Yan. 2013 · 2013
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Giving to others and the association between stress and mortality
Michael J Poulin, Stephanie L Brown, Amanda J Dillard, and Dylan M Smith. 2013 · 2013
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D. Manning, Andrew Ng, and Christopher Potts. 2013 · 2013
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Exploring demographic language variations to improve multilingual sentiment analysis in social media
Svitlana Volkova, Theresa Wilson, and David Yarowsky. 2013 · 2013
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Identifying empathetic messages in online health communities
Hamed Khanpour, Cornelia Caragea, and Prakhar Biyani. 2017 · 2017
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2017 · 2017
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Understanding and predicting empathic behavior in counseling therapy
Verónica Pérez-Rosas, Rada Mihalcea, Kenneth Resnicow, Satinder Singh, and Lawrence An. 2017 · 2017
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SemEval-2017 task 4: Sentiment analysis in twitter
Sara Rosenthal, Noura Farra, and Preslav Nakov. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Annotating and modeling empathy in spoken conversations
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David Bamman, Chris Dyer, and Noah A. Smith. 2014 · 2014
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Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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Predicting therapist empathy in motivational interviews using language features inspired by psycholinguistic norms
James Gibson, Nikolaos Malandrakis, Francisco Romero, David C Atkins, and Shrikanth S Narayanan. 2015 · 2015
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Demographic factors improve classification performance
Dirk Hovy. 2015 · 2015
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Improving named entity recognition in tweets via detecting non-standard words
Chen Li and Yang Liu. 2015 · 2015
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Aligning books and movies: Towards story-like visual explanations by watching movies and reading books
Yukun Zhu, Ryan Kiros, Rich Zemel, Ruslan Salakhutdinov, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Firoj Alam, Morena Danieli, and Giuseppe Riccardi. 2018 · 2018
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Modeling empathy and distress in reaction to news stories
Sven Buechel, Anneke Buffone, Barry Slaff, Lyle Ungar, and João Sedoc. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Adversarial removal of demographic attributes from text data
Yanai Elazar and Yoav Goldberg. 2018 · 2018
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Mining cross-cultural differences and similarities in social media
Bill Yuchen Lin, Frank F. Xu, Kenny Zhu, and Seung-won Hwang. 2018 · 2018
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Cross-cultural differences in language markers of depression online
Kate Loveys, Jonathan Torrez, Alex Fine, Glen Moriarty, and Glen Coppersmith. 2018 · 2018
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Towards augmenting crisis counselor training by improving message retrieval
Orianna Demasi, Marti A. Hearst, and Benjamin Recht. 2019 · 2019
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MoEL: Mixture of empathetic listeners
Zhaojiang Lin, Andrea Madotto, Jamin Shin, Peng Xu, and Pascale Fung. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Towards empathetic open-domain conversation models: A new benchmark and dataset
Hannah Rashkin, Eric Smith, Margaret Li, and Y-Lan Boureau. 2019 · 2019
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How to fine-tune bert for text classification?
Chi Sun, Xipeng Qiu, Yige Xu, and Xuanjing Huang. 2019 · 2019
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