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Memory-Guided Multi-View Multi-Domain Fake News Detection (2206.12808v1)

Published 26 Jun 2022 in cs.CL, cs.AI, and cs.LG

Abstract: The wide spread of fake news is increasingly threatening both individuals and society. Great efforts have been made for automatic fake news detection on a single domain (e.g., politics). However, correlations exist commonly across multiple news domains, and thus it is promising to simultaneously detect fake news of multiple domains. Based on our analysis, we pose two challenges in multi-domain fake news detection: 1) domain shift, caused by the discrepancy among domains in terms of words, emotions, styles, etc. 2) domain labeling incompleteness, stemming from the real-world categorization that only outputs one single domain label, regardless of topic diversity of a news piece. In this paper, we propose a Memory-guided Multi-view Multi-domain Fake News Detection Framework (M$3$FEND) to address these two challenges. We model news pieces from a multi-view perspective, including semantics, emotion, and style. Specifically, we propose a Domain Memory Bank to enrich domain information which could discover potential domain labels based on seen news pieces and model domain characteristics. Then, with enriched domain information as input, a Domain Adapter could adaptively aggregate discriminative information from multiple views for news in various domains. Extensive offline experiments on English and Chinese datasets demonstrate the effectiveness of M$3$FEND, and online tests verify its superiority in practice. Our code is available at https://github.com/ICTMCG/M3FEND.

Overview of "Bare Advanced Demo of IEEEtran.cls for IEEE Computer Society Journals"

The paper "Bare Advanced Demo of IEEEtran.cls for IEEE Computer Society Journals" authored by Michael Shell et al., serves as a comprehensive demonstration of the IEEEtran.cls file—a LaTeX class file widely used for preparing IEEE Computer Society journal papers. While the document primarily functions as a template or starting file aimed at assisting authors in typesetting their work according to IEEE standards, it implicitly illustrates the capabilities and structure of the IEEEtran.cls.

Structural and Formatting Features

The template document delivers an archetype for structuring IEEE Computer Society journal papers. It elucidates the organization of sections and subsections, demonstrating the appropriate hierarchical structure to maintain a coherent scholarly narrative. Key elements such as title construction, author and affiliation presentation, and abstract and keyword formatting are exemplified, providing clear guidance on aligning with IEEE's rigorous formatting standards.

A critical focus of the paper is on proper handling of metadata such as the use of \verb|\markboth| for running head entries, which enables dynamic and context-aware headers. Additionally, the paper underlines the importance of correctly implementing the \verb|\IEEEtitleabstractindextext| and \verb|\IEEEdisplaynontitleabstractindextext| commands to manage the abstract and index text effectively for both peer-reviewed and final publication documents.

Technical Proficiencies and Commands

The document is heavily oriented towards demonstrating various commands and environments integral to IEEEtran.cls. It provides examples of:

  • List generation including both itemized and enumerated lists
  • Incorporating hyperlinks through the use of hyperref packages tailored for IEEE compatibility
  • Displaying algorithms and equations using appropriate mathematical environments

It also showcases the ability to fine-tune document aesthetics, such as adjusting hyphenation and employing specialized macros for consistent author and affiliation formatting across different manuscript versions.

Implications and Future Considerations

The utility of such a document lies in its ability to streamline the manuscript preparation process for authors targeting IEEE publications, ensuring consistency and adherence to a recognized publication standard. From a theoretical standpoint, it reinforces the necessity and value of standardized templates in facilitating knowledge dissemination across complex fields such as electrical and computer engineering.

Considering future developments in tools and automation within document processing, this template serves as a foundational artifact which could be expanded with additional features such as automated syntax validation or integration with collaborative writing platforms. Continuous updates to reflect evolving formatting guidelines and compatibility with new LaTeX packages would further enhance its relevance and utility in the manuscript submission pipeline.

In conclusion, while the paper serves a utilitarian purpose of guiding proper document preparation using IEEEtran.cls, it inadvertently plays a critical role in reducing bottlenecks associated with format-related revisions, thus enabling researchers to focus on content quality and innovation.

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Authors (8)
  1. Yongchun Zhu (35 papers)
  2. Qiang Sheng (29 papers)
  3. Juan Cao (73 papers)
  4. Qiong Nan (5 papers)
  5. Kai Shu (88 papers)
  6. Minghui Wu (21 papers)
  7. Jindong Wang (150 papers)
  8. Fuzhen Zhuang (97 papers)
Citations (66)