Fetching the paper…
Reading the bibliography…
This paper describes our participation in Task 5 track 2 of SemEval 2017 to predict the sentiment of financial news headlines for a specific company on a continuous scale between -1 and 1.
Support vector regression machines
Harris Drucker, Christopher JC Burges, Linda Kaufman, Alex Smola, Vladimir Vapnik, et al. 1997 · 1997
Earlier work this paper cites.
Long short-term memory
Sepp Hochreiter and Jürgen Schmidhuber. 1997 · 1997
Earlier work this paper cites.
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
Peter D Turney. 2002 · 2002
Earlier work this paper cites.
Sentiment analysis: Capturing favorability using natural language processing
Tetsuya Nasukawa and Jeonghee Yi. 2003 · 2003
Earlier work this paper cites.
Framewise phoneme classification with bidirectional lstm and other neural network architectures
Alex Graves and Jürgen Schmidhuber. 2005 · 2005
Earlier work this paper cites.
When is a liability not a liability? textual analysis, dictionaries, and 10-ks
Tim Loughran and Bill McDonald. 2011 · 2011
Earlier work this paper cites.
Scikit-learn: Machine learning in python
Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, et al. 2011 · 2011
Cited alongside, same era.
Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
Cited alongside, same era.
Semeval-2014 task 4: Aspect based sentiment analysis
Maria Pontiki, Dimitris Galanis, John Pavlopoulos, Harris Papageorgiou, Ion Androutsopoulos, and Suresh Manandhar. 2014 · 2014
Cited alongside, same era.
Tensorflow: Large-scale machine learning on heterogeneous distributed systems
Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et al. 2016 · 2016
Cited alongside, same era.
Xrce at semeval-2016 task 5: Feedbacked ensemble modelling on syntactico-semantic knowledge for aspect based sentiment analysis
Domain adaptation using stock market prices to refine sentiment dictionaries
Andrew Moore, Paul Rayson, and Steven Young. 2016 · 2016
Later among the works it cites.
Leverage financial news to predict stock price movements using word embeddings and deep neural networks
Yangtuo Peng and Hui Jiang. 2016 · 2016
Later among the works it cites.
A hierarchical model of reviews for aspect-based sentiment analysis
Sebastian Ruder, Parsa Ghaffari, and G. John Breslin. 2016 · 2016
Later among the works it cites.
Attention-based lstm for aspect-level sentiment classification
Yequan Wang, Minlie Huang, xiaoyan zhu, and Li Zhao. 2016 · 2016
Later among the works it cites.
Semeval-2017 task 5: Fine-grained sentiment analysis on financial microblogs and news
Keith Cortis, Andre Freitas, Tobias Daudert, Manuela Huerlimann, Manel Zarrouk, and Brian Davis. 2017 · 2017
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Caroline Brun, Julien Perez, and Claude Roux. 2016 · 2016
Cited alongside, same era.
Iit-tuda at semeval-2016 task 5: Beyond sentiment lexicon: Combining domain dependency and distributional semantics features for aspect based sentiment analysis
Ayush Kumar, Sarah Kohail, Amit Kumar, Asif Ekbal, and Chris Biemann. 2016 · 2016
Cited alongside, same era.
Siavash Kazemian, Shunan Zhao, and Gerald Penn. 2016 · 2094
Closest in time.