Meta-path-based fake news detection leveraging multi-level social context information복합적 소셜네트워크 정보를 활용한 메타패스 기반 가짜 뉴스 탐지

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dc.contributor.advisorShin, Seungwon-
dc.contributor.advisor신승원-
dc.contributor.authorCui, Jian-
dc.date.accessioned2023-06-26T19:34:14Z-
dc.date.available2023-06-26T19:34:14Z-
dc.date.issued2022-
dc.identifier.urihttp://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=997254&flag=dissertationen_US
dc.identifier.urihttp://hdl.handle.net/10203/309940-
dc.description학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2022.2,[iv, 36 p. :]-
dc.description.abstractFake news, false or misleading information presented as news, has a significant impact on many aspects of society, such as in politics or healthcare domains. Due to the deceiving nature of fake news, applying Natural Language Processing (NLP) techniques to the news content alone is insufficient. Therefore, more information is required to improve fake news detection, such as the multi-level social context (news publishers and engaged users in social media) information and the temporal information of user engagement. The proper usage of this information, however, introduces three chronic difficulties: 1) multi-level social context information is hard to be used without information loss, 2) temporal information is hard to be used along with multi-level social context information, 3) news representation with multi- level social context and temporal information is hard to be learned in an end-to-end manner. To overcome all three difficulties, we propose a novel fake news detection framework, Hetero-SCAN. We use Meta- Path to extract meaningful multi-level social context information without loss. Meta-Path, a composite relation connecting two node types, is proposed to capture the semantics in the heterogeneous graph. We then propose Meta-Path instance encoding and aggregation methods to capture the temporal information of user engagement and learn news representation end-to-end. According to our experiment, Hetero-SCAN yields significant performance improvement over state-of-the-art fake news detection methods.-
dc.languageeng-
dc.publisher한국과학기술원-
dc.titleMeta-path-based fake news detection leveraging multi-level social context information-
dc.title.alternative복합적 소셜네트워크 정보를 활용한 메타패스 기반 가짜 뉴스 탐지-
dc.typeThesis(Master)-
dc.identifier.CNRN325007-
dc.description.department한국과학기술원 :전기및전자공학부,-
dc.contributor.alternativeauthor최건-
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