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    Information contagion in temporal human networks with heterogeneous susceptibility

    Author
    Trujillo, Milo Zappa
    View/Open
    180033_Trujillo_rpi_0185N_11664.pdf (5.135Mb)
    Other Contributors
    Gao, Jianxi; Adali, Sibel; Holzbauer, Buster;
    Date Issued
    2020-05
    Subject
    Computer science
    Degree
    MS;
    Terms of Use
    This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.;
    Metadata
    Show full item record
    URI
    https://hdl.handle.net/20.500.13015/2519
    Abstract
    Information Cascades are propagation patterns in human networks where information such as political propaganda, rumors, or fashion trends, emanate from one or more starting points and are either accepted or rejected by each connected member of a community. The decisions made by individuals either govern a large ripple through the community, or prevent significant changes from occurring, making Information Cascades of avid interest within economics and network science. Since Information Cascades have similar behavior to the well studied field of epidemiology, many Cascades are modeled with disease propagation models like the Susceptibility, Infection, and Recovery (SIR) model. In this thesis we argue that such generic models are insufficient for predicting information spread in human behavioral networks, because they do not represent temporal availability of communication and individual variations in susceptibility to peer-pressure. We propose a new model wherein agents have heterogeneous activity periods and activation thresholds, representing individual susceptibility to peer-pressure. By applying this model to networks with a range of topologies, as well as real-world networks, we are able to more accurately represent human behavior in a variety of communities.;
    Description
    May 2020; School of Science
    Department
    Dept. of Computer Science;
    Publisher
    Rensselaer Polytechnic Institute, Troy, NY
    Relationships
    Rensselaer Theses and Dissertations Online Collection;
    Access
    Restricted to current Rensselaer faculty, staff and students. Access inquiries may be directed to the Rensselaer Libraries.;
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