Natural Language Contents Evaluation System for Detecting Fake News using Deep Learning

Ye Chan Ahn, Chang Sung Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This Recently, a lot of information is spreading rapidly on SNS. Inaccurate communication of news media includes fears about unreliable sources and fake news that lacks confirmation of facts. Fake news is spread through SNS, causing social confusion and further economic loss. The purpose of the news is accurate information transmission. In this regard, it is very important to judge the discrepancies in the contents of the text and the distorted reports. We try to solve the problem of judging whether the sentence to be verified is correct after collecting the facts. This paper defines the problem of extracting the related sentences from the input sentence in Fact Data Corpus which is assumed to be fact and judging whether the extracted sentence and the input sentence are true or false. In the various NLP tasks, we create a Korean-specific pre-Training model using state-of-The-Art BERT. Using this model, fine-Tuning is performed to match the data set detected by Korean fake news. The AUROC score of 83.8% is derived from the test set generated using the fine-Tuned model.

Original languageEnglish
Title of host publicationJCSSE 2019 - 16th International Joint Conference on Computer Science and Software Engineering
Subtitle of host publicationKnowledge Evolution Towards Singularity of Man-Machine Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages289-292
Number of pages4
ISBN (Electronic)9781728107196
DOIs
Publication statusPublished - 2019 Jul
Event16th International Joint Conference on Computer Science and Software Engineering, JCSSE 2019 - Chonburi, Thailand
Duration: 2019 Jul 102019 Jul 12

Publication series

NameJCSSE 2019 - 16th International Joint Conference on Computer Science and Software Engineering: Knowledge Evolution Towards Singularity of Man-Machine Intelligence

Conference

Conference16th International Joint Conference on Computer Science and Software Engineering, JCSSE 2019
CountryThailand
CityChonburi
Period19/7/1019/7/12

Keywords

  • BERT
  • Fake news Detection
  • NLP

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Information Systems and Management

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  • Cite this

    Ahn, Y. C., & Jeong, C. S. (2019). Natural Language Contents Evaluation System for Detecting Fake News using Deep Learning. In JCSSE 2019 - 16th International Joint Conference on Computer Science and Software Engineering: Knowledge Evolution Towards Singularity of Man-Machine Intelligence (pp. 289-292). [8864171] (JCSSE 2019 - 16th International Joint Conference on Computer Science and Software Engineering: Knowledge Evolution Towards Singularity of Man-Machine Intelligence). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/JCSSE.2019.8864171