skip to main content
10.1145/1458527.1458530acmconferencesArticle/Chapter ViewAbstractPublication PagesthewebconfConference Proceedingsconference-collections
keynote

Information credibility analysis of web content

Published: 30 October 2008 Publication History

Abstract

General users write daily news about themselves and post information they consider interesting as digital documents for blogs and SNS. Such digital content includes both valuable information as well as worthless, false, and demagogic information. Ordinary web search engines can display web pages in a particular order. The ranking method evaluates the score of web content and generates a ranked list. The top-ranked web content on search engines is often relevant to the user's query, though, in some cases, the content may not be credible or valuable. Nevertheless, readers often trust the authenticity of the displayed information. Even if users believe that the content is useful, the search engine cannot evaluate the retrieved digital content, and users have to retrieve a variety of content using different keywords. The need for an information analysis technology that helps find credible and valuable information from large amounts of Web content is progressively growing.
In Japan, the NICT (National Institute of Information and Communications Technology) initiated the ''Information Credibility Criteria Project'' in 2oo6, and the MIC (Ministry of Internal Affairs and Communications), too, initiated the ''Research and Development of Information Credibility Verification Technology for Telecommunication Service'' in 2007.
The NICT's project addresses the issue of information credibility by analyzing credibility based on the following criteria: (1) content, (2) sender, (3) appearance, and (4) authenticity of content. We believe that the understanding of texts by a machine is important and that an NLP (Natural Language Processing) approach is very effective in evaluating the credibility criteria. The MIC's project aims to develop methods to analyze not only text information but also multimedia content using NLP, information retrieval and data mining approaches. By using different methods for analyzing the information credibility criteria, credible information can be acquired, which eventually becomes valuable knowledge.
This talk will throw light on the activities of both projects in Japan.

Cited By

View all

Index Terms

  1. Information credibility analysis of web content

    Recommendations

    Comments

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    WICOW '08: Proceedings of the 2nd ACM workshop on Information credibility on the web
    October 2008
    100 pages
    ISBN:9781605582597
    DOI:10.1145/1458527
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 30 October 2008

    Permissions

    Request permissions for this article.

    Check for updates

    Author Tags

    1. information credibility
    2. information retrieval
    3. nlp

    Qualifiers

    • Keynote

    Conference

    CIKM08
    CIKM08: Conference on Information and Knowledge Management
    October 30, 2008
    California, Napa Valley, USA

    Acceptance Rates

    Overall Acceptance Rate 9 of 19 submissions, 47%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)3
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 06 Jan 2025

    Other Metrics

    Citations

    Cited By

    View all

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media