Improving the Accuracy of Pre-trained Word Embeddings for Sentiment Analysis

23 November 2017

Papers citing "Improving the Accuracy of Pre-trained Word Embeddings for Sentiment Analysis"

9 / 9 papers shown

Title
On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition Christophe Cerisara Pavel Král Ladislav Lenc 51 56 0 22 Oct 2020
SemEval-2015 Task 10: Sentiment Analysis in Twitter Sara Rosenthal Saif M. Mohammad Preslav Nakov Alan Ritter S. Kiritchenko Veselin Stoyanov 69 422 0 05 Dec 2019
Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification Jan Deriu Aurelien Lucchi V. D. Luca Aliaksei Severyn Simon Müller Mark Cieliebak Thomas Hofmann Martin Jaggi 64 133 0 07 Mar 2017
Semantics derived automatically from language corpora contain human-like biases Aylin Caliskan J. Bryson Arvind Narayanan 223 2,678 0 25 Aug 2016
A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification Ye Zhang Byron C. Wallace AAML 124 1,201 0 13 Oct 2015
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 644 13,432 0 25 Aug 2014
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 402 33,573 0 16 Oct 2013
NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets Saif M. Mohammad S. Kiritchenko Xiao-Dan Zhu 87 1,075 0 28 Aug 2013
Efficient Estimation of Word Representations in Vector Space Tomas Mikolov Kai Chen G. Corrado J. Dean 3DV 693 31,553 0 16 Jan 2013