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Identify influential spreaders in online social networks based on social meta path and PageRank

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86099088" target="_blank" >RIV/61989100:27240/16:86099088 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1007/978-3-319-42345-6_5" target="_blank" >http://dx.doi.org/10.1007/978-3-319-42345-6_5</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-319-42345-6_5" target="_blank" >10.1007/978-3-319-42345-6_5</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Identify influential spreaders in online social networks based on social meta path and PageRank

  • Original language description

    Identifying "influential spreader" is finding a subset of individuals in the social network, so that when information injected into this subset, it is spread most broadly to the rest of the network individuals. The determination of the information influence degree of individual plays an important role in online social networking. Once there is a list of individuals who have high influence, the marketers can access these individuals and seek them to impress, bribe or somehow make them spread up the good information for their business as well as their product in marketing campaign. In this paper, according to the idea "Information can be spread between two unconnected users in the network as long as they both check-in at the same location", we proposed an algorithm called SMPRank (Social Meta Path Rank) to identify individuals with the largest influence in complex online social networks. The experimental results show that SMPRank performs better than Weighted LeaderRank because of the ability to determinate more influential spreaders. (C) Springer International Publishing Switzerland 2016.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2016

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). volume 9795

  • ISBN

    978-3-319-42344-9

  • ISSN

    0302-9743

  • e-ISSN

  • Number of pages

    11

  • Pages from-to

    51-61

  • Publisher name

    Springer

  • Place of publication

    Cham

  • Event location

    Ho Či Minovo Město

  • Event date

    Aug 2, 2016

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article