FAMOUS: Fake News Detection Model Based on Unified Key Sentence Information

Namwon Kim, Deokjin Seo, Chang Sung Jeong

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

7 Citations (Scopus)

Abstract

Fake news detection causes a challenging problem due to the great influence of communication media over the public. In this paper, we shall present a new fake news detection model using unified key sentence information which can efficiently perform sentence matching between question and article by using key sentence retrieval based on bilateral multi perspective matching model. Our model makes use of one unified word vector for the key sentences of article by extracting them to the question from article and then merging the word vector for each key sentence. It can efficiently perform the sentence matching by executing matching operations between the contextual information obtained from the word vectors of question and key sentences through bidirectional long short term memory. Our model shows the competitive performance for fake news detection on the Korean article dataset over the previous result.

Original languageEnglish
Title of host publicationICSESS 2018 - Proceedings of 2018 IEEE 9th International Conference on Software Engineering and Service Science
EditorsLi Wenzheng, M. Surendra Prasad Babu
PublisherIEEE Computer Society
Pages617-620
Number of pages4
ISBN (Electronic)9781538665640
DOIs
Publication statusPublished - 2018 Jul 2
Event9th IEEE International Conference on Software Engineering and Service Science, ICSESS 2018 - Beijing, China
Duration: 2018 Nov 232018 Nov 25

Publication series

NameProceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
Volume2018-November
ISSN (Print)2327-0586
ISSN (Electronic)2327-0594

Conference

Conference9th IEEE International Conference on Software Engineering and Service Science, ICSESS 2018
Country/TerritoryChina
CityBeijing
Period18/11/2318/11/25

Bibliographical note

Funding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1AlB03035461), the Brain Korea 21 Plus Project in 2018, and the Institute for Information & Communications Technology Promotion(IITP) grant funded by the Korea government (MSIT) (No. 2018-0-00739, Deep learning-based natural language contents evaluation technology for detecting fake news).

Funding Information:
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1AlB03035461).

Publisher Copyright:
© 2018 IEEE.

Keywords

  • fake news detectiont
  • key sentence retrieval
  • natural language processing
  • sentence matching

ASJC Scopus subject areas

  • Software

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