External Content-dependent Features for Web Credibility Evaluation

Kazuyoshi Ootani, Hayato Yamana

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

    Abstract

    Unreliable web pages such as fake news has become a global problem in big data era. The motivation to publish fake news is often for profit; for example, earning advertisement income by putting ads on their web pages. In this paper, we focus on different usage of HTML source tags between reliable and unreliable web pages, then propose new features for predicting their credibility. The experimental result shows that our proposed features increase accuracy when used together with previously proposed Contents features.

    Original languageEnglish
    Title of host publicationProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018
    EditorsYang Song, Bing Liu, Kisung Lee, Naoki Abe, Calton Pu, Mu Qiao, Nesreen Ahmed, Donald Kossmann, Jeffrey Saltz, Jiliang Tang, Jingrui He, Huan Liu, Xiaohua Hu
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages5414-5416
    Number of pages3
    ISBN (Electronic)9781538650356
    DOIs
    Publication statusPublished - 2019 Jan 22
    Event2018 IEEE International Conference on Big Data, Big Data 2018 - Seattle, United States
    Duration: 2018 Dec 102018 Dec 13

    Publication series

    NameProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

    Conference

    Conference2018 IEEE International Conference on Big Data, Big Data 2018
    CountryUnited States
    CitySeattle
    Period18/12/1018/12/13

    Fingerprint

    World Wide Web
    Websites
    HTML
    Profitability
    Big data

    Keywords

    • fake sites;
    • unreliable web pages
    • web credibility

    ASJC Scopus subject areas

    • Computer Science Applications
    • Information Systems

    Cite this

    Ootani, K., & Yamana, H. (2019). External Content-dependent Features for Web Credibility Evaluation. In Y. Song, B. Liu, K. Lee, N. Abe, C. Pu, M. Qiao, N. Ahmed, D. Kossmann, J. Saltz, J. Tang, J. He, H. Liu, ... X. Hu (Eds.), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018 (pp. 5414-5416). [8622398] (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigData.2018.8622398

    External Content-dependent Features for Web Credibility Evaluation. / Ootani, Kazuyoshi; Yamana, Hayato.

    Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. ed. / Yang Song; Bing Liu; Kisung Lee; Naoki Abe; Calton Pu; Mu Qiao; Nesreen Ahmed; Donald Kossmann; Jeffrey Saltz; Jiliang Tang; Jingrui He; Huan Liu; Xiaohua Hu. Institute of Electrical and Electronics Engineers Inc., 2019. p. 5414-5416 8622398 (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018).

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

    Ootani, K & Yamana, H 2019, External Content-dependent Features for Web Credibility Evaluation. in Y Song, B Liu, K Lee, N Abe, C Pu, M Qiao, N Ahmed, D Kossmann, J Saltz, J Tang, J He, H Liu & X Hu (eds), Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018., 8622398, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, Institute of Electrical and Electronics Engineers Inc., pp. 5414-5416, 2018 IEEE International Conference on Big Data, Big Data 2018, Seattle, United States, 18/12/10. https://doi.org/10.1109/BigData.2018.8622398
    Ootani K, Yamana H. External Content-dependent Features for Web Credibility Evaluation. In Song Y, Liu B, Lee K, Abe N, Pu C, Qiao M, Ahmed N, Kossmann D, Saltz J, Tang J, He J, Liu H, Hu X, editors, Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 5414-5416. 8622398. (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018). https://doi.org/10.1109/BigData.2018.8622398
    Ootani, Kazuyoshi ; Yamana, Hayato. / External Content-dependent Features for Web Credibility Evaluation. Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018. editor / Yang Song ; Bing Liu ; Kisung Lee ; Naoki Abe ; Calton Pu ; Mu Qiao ; Nesreen Ahmed ; Donald Kossmann ; Jeffrey Saltz ; Jiliang Tang ; Jingrui He ; Huan Liu ; Xiaohua Hu. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 5414-5416 (Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018).
    @inproceedings{c440cf9f476d4201bfd16049cc7b0379,
    title = "External Content-dependent Features for Web Credibility Evaluation",
    abstract = "Unreliable web pages such as fake news has become a global problem in big data era. The motivation to publish fake news is often for profit; for example, earning advertisement income by putting ads on their web pages. In this paper, we focus on different usage of HTML source tags between reliable and unreliable web pages, then propose new features for predicting their credibility. The experimental result shows that our proposed features increase accuracy when used together with previously proposed Contents features.",
    keywords = "fake sites;, unreliable web pages, web credibility",
    author = "Kazuyoshi Ootani and Hayato Yamana",
    year = "2019",
    month = "1",
    day = "22",
    doi = "10.1109/BigData.2018.8622398",
    language = "English",
    series = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",
    publisher = "Institute of Electrical and Electronics Engineers Inc.",
    pages = "5414--5416",
    editor = "Yang Song and Bing Liu and Kisung Lee and Naoki Abe and Calton Pu and Mu Qiao and Nesreen Ahmed and Donald Kossmann and Jeffrey Saltz and Jiliang Tang and Jingrui He and Huan Liu and Xiaohua Hu",
    booktitle = "Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018",

    }

    TY - GEN

    T1 - External Content-dependent Features for Web Credibility Evaluation

    AU - Ootani, Kazuyoshi

    AU - Yamana, Hayato

    PY - 2019/1/22

    Y1 - 2019/1/22

    N2 - Unreliable web pages such as fake news has become a global problem in big data era. The motivation to publish fake news is often for profit; for example, earning advertisement income by putting ads on their web pages. In this paper, we focus on different usage of HTML source tags between reliable and unreliable web pages, then propose new features for predicting their credibility. The experimental result shows that our proposed features increase accuracy when used together with previously proposed Contents features.

    AB - Unreliable web pages such as fake news has become a global problem in big data era. The motivation to publish fake news is often for profit; for example, earning advertisement income by putting ads on their web pages. In this paper, we focus on different usage of HTML source tags between reliable and unreliable web pages, then propose new features for predicting their credibility. The experimental result shows that our proposed features increase accuracy when used together with previously proposed Contents features.

    KW - fake sites;

    KW - unreliable web pages

    KW - web credibility

    UR - http://www.scopus.com/inward/record.url?scp=85062621901&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=85062621901&partnerID=8YFLogxK

    U2 - 10.1109/BigData.2018.8622398

    DO - 10.1109/BigData.2018.8622398

    M3 - Conference contribution

    T3 - Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

    SP - 5414

    EP - 5416

    BT - Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

    A2 - Song, Yang

    A2 - Liu, Bing

    A2 - Lee, Kisung

    A2 - Abe, Naoki

    A2 - Pu, Calton

    A2 - Qiao, Mu

    A2 - Ahmed, Nesreen

    A2 - Kossmann, Donald

    A2 - Saltz, Jeffrey

    A2 - Tang, Jiliang

    A2 - He, Jingrui

    A2 - Liu, Huan

    A2 - Hu, Xiaohua

    PB - Institute of Electrical and Electronics Engineers Inc.

    ER -