International Conference on Computational Linguistics · 2016 · 36 citations · 12 references
ComputingPolitical CommunicationVisualizationComputational LinguisticsNatural Language ProcessingText AnalyticsOpinion MiningPolitical Communication AnalyticsSemantic NetworksSentiment AnalysisText VisualizationWord EmbeddingsArgument VisualizationArgumentation VisualizationDiscourse VisualizationLearned Feature EmbeddingsScatter PlotsSentiment VisualizationText NetworksTopic Visualization
This paper presents WordForce, a system powered by the state of the art neural network model to visualize the learned user-dependent word embeddings from each post according to the post content and its engaged users. It generates the scatter plots to show the force of a word, i.e., whether the semantics of word embeddings from posts of different stances are clearly separated from the aspect of this controversial word. In addition, WordForce provides the dispersion and the distance of word embeddings from posts of different stance groups, and proposes the most controversial words accordingly to show clues to what people argue about in a debate.
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Laurens van der Maaten, Geoffrey E. Hinton · Journal of Machine Learning Research · 2008 · 35.7K citations
Distributed Representations of Words and Phrases and their Compositionality
Tomáš Mikolov, Ilya Sutskever, Kai Chen et al. · arXiv (Cornell University) · 2013 · 18.1K citations · Full text
Convolutional Neural Networks for Sentence Classification