Determining the Relative Importance of Webpages Based on Social Signals Using the Social Score and the Potential Role of the Social Score in an Asynchronous Social Search Engine

M. Buijs, M. Spruit

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    There are many ways to determine the relative importance of webpages. Specifically, a method that has proven to be very successful in practice is to value a webpage based on its position in the hyperlinked graph of the web. However, there is no generally applicable algorithm to determine the value of webpages based on an arbitrary number social signals such as likes, tweets and shares. By taking such social signals into account a more democratic method arises to determine the value of webpages. In this article we propose an algorithm named the Social Score that takes into account an arbitrary number of social signals to determine the relative importance of a webpage. Also, we present a worldwide top fifty of webpages based on the Social Score. Last, the potential role of the Social Score in an asynchronous Social Search engine is evaluated.
    Original languageEnglish
    Title of host publicationKnowledge Discovery, Knowledge Engineering and Knowledge Management
    Subtitle of host publication6th International Joint Conference, IC3K 2014, Rome, Italy, October 21-24, 2014, Revised Selected Papers
    EditorsA. Fred, J. Dietz, D. Aveiro, K. Liu, J. Filipe
    PublisherSpringer
    Pages118–131
    ISBN (Electronic)978-3-319-25840-9
    ISBN (Print)978-3-319-25839-3
    DOIs
    Publication statusPublished - 2015

    Publication series

    NameCommunications in Computer and Information Science
    PublisherSpringer
    Volume553
    ISSN (Print)1865-0929

    Keywords

    • Social Score
    • Asynchronous Social Search
    • PageRank
    • Web search
    • Top-K ranking
    • Quality assessment
    • Data analytics
    • Information extraction

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