Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets

Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets

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...

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Main Authors: Deng, Ran, Duzhin, Fedor
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2023
Subjects:
Science::Mathematics
Topological Data Analysis
Persistent Homology;
Online Access:https://hdl.handle.net/10356/164231
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Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-164231
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spelling sg-ntu-dr.10356-1642312023-02-28T20:07:56Z Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets Deng, Ran Duzhin, Fedor School of Physical and Mathematical Sciences Science::Mathematics Topological Data Analysis Persistent Homology; 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. Published version 2023-01-10T06:58:40Z 2023-01-10T06:58:40Z 2022 Journal Article Deng, R. & Duzhin, F. (2022). Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets. Big Data and Cognitive Computing, 6(3). https://dx.doi.org/10.3390/bdcc6030074 2504-2289 https://hdl.handle.net/10356/164231 10.3390/bdcc6030074 2-s2.0-85134607310 3 6 en Big Data and Cognitive Computing © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Science::Mathematics
Topological Data Analysis
Persistent Homology;
spellingShingle Science::Mathematics
Topological Data Analysis
Persistent Homology;
Deng, Ran
Duzhin, Fedor
Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets
description 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.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Deng, Ran
Duzhin, Fedor
format Article
author Deng, Ran
Duzhin, Fedor
author_sort Deng, Ran
title Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets
title_short Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets
title_full Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets
title_fullStr Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets
title_full_unstemmed Topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets
title_sort topological data analysis helps to improve accuracy of deep learning models for fake news detection trained on very small training sets
publishDate 2023
url https://hdl.handle.net/10356/164231
_version_ 1759855342349451264

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