Topological Data Analysis Helps to Improve Accuracy of Deep Learning Models for Fake News Detection Trained on Very Small Training Sets
Ran Deng, Fedor Duzhin
Abstract
Topological data analysis has recently found applications in various areas of science, such as computer vision and understanding of protein folding. However, applications of topological data analysis to natural language processing remain under-researched. This study applies topological data analysis to a particular natural language processing task: fake news detection. We have found that deep learning models are more accurate in this task than topological data analysis. However, assembling a deep learning model with topological data analysis significantly improves the model’s accuracy if the available training set is very small.
Topics & Concepts
Topological data analysisComputer scienceTask (project management)Training setSet (abstract data type)Data setDeep learningArtificial intelligenceTopology (electrical circuits)Folding (DSP implementation)Machine learningAlgorithmMathematicsEngineeringCombinatoricsProgramming languageSystems engineeringElectrical engineeringTopological and Geometric Data AnalysisHomotopy and Cohomology in Algebraic TopologyNeuroinflammation and Neurodegeneration Mechanisms