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Real-Time News Cer tification System on Sina Weibo

Published: 18 May 2015 Publication History

Abstract

In this paper, we propose a novel framework for real-time news certification. Traditional methods detect rumors on message-level and analyze the credibility of one tweet. However, in most occasions, we only remember the keywords of an event and it's hard for us to completely describe an event in a tweet. Based on the keywords of an event, we gather related microblogs through a distributed data acquisition system which solves the real-time processing needs. Then, we build an ensemble model that combine user-based, propagation-based and content-based model. The experiments show that our system can give a response at 35 seconds on average per query which is critical for real-time system. Most importantly, our ensemble model boost the performance. We also offer some important information such as key users, key microblogs and timeline of events for further investigation of an event.Our system is already deployed in the Xihua News Agency for half a year. To the best of our knowledge, this is the first real-time news certification system for verifying social media contents.

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  1. Real-Time News Cer tification System on Sina Weibo

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    cover image ACM Other conferences
    WWW '15 Companion: Proceedings of the 24th International Conference on World Wide Web
    May 2015
    1602 pages
    ISBN:9781450334730
    DOI:10.1145/2740908

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    • IW3C2: International World Wide Web Conference Committee

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 18 May 2015

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    Author Tags

    1. ensemble model
    2. real-time system
    3. rumor detection

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    • Research-article

    Funding Sources

    • National Nature Science Foundation of China
    • National High Technology Research and Development Program of China

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    WWW '15
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    • IW3C2

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    Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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    • (2024)MMDFND: Multi-modal Multi-Domain Fake News DetectionProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681317(1178-1186)Online publication date: 28-Oct-2024
    • (2024)Systemization of Knowledge (SoK): Creating a Research Agenda for Human-Centered Real-Time Risk Detection on Social Media PlatformsProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642315(1-21)Online publication date: 11-May-2024
    • (2023)Toward News Authenticity: Synthesizing Natural Language Processing and Human Expert Opinion to Evaluate NewsIEEE Access10.1109/ACCESS.2023.324148311(11405-11421)Online publication date: 2023
    • (2023)Fake news detection using dual BERT deep neural networksMultimedia Tools and Applications10.1007/s11042-023-17115-w83:15(43831-43848)Online publication date: 16-Oct-2023
    • (2023)Fake News Detection Using LSTM-Based Deep Learning Approach and Word Embedding Feature ExtractionProceedings of the NIELIT's International Conference on Communication, Electronics and Digital Technology10.1007/978-981-99-1699-3_8(129-141)Online publication date: 27-Jun-2023
    • (2023)Social Network Analysis for Disinformation DetectionMachine Learning for Data Science Handbook10.1007/978-3-031-24628-9_30(681-701)Online publication date: 26-Feb-2023
    • (2022)Seeing Should Probably Not Be Believing: The Role of Deceptive Support in COVID-19 Misinformation on TwitterJournal of Data and Information Quality10.1145/354691415:1(1-26)Online publication date: 28-Dec-2022
    • (2022)Memory-Guided Multi-View Multi-Domain Fake News DetectionIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3185151(1-14)Online publication date: 2022
    • (2022)Characterizing multi-domain false news and underlying user effects on Chinese WeiboInformation Processing and Management: an International Journal10.1016/j.ipm.2022.10295959:4Online publication date: 1-Jul-2022
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