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  • Sending messages in social networks

    Author(s)
    Cristani, M
    Olivieri, F
    Tomazzoli, C
    Governatori, G
    Griffith University Author(s)
    Olivieri, Francesco
    Year published
    2018
    Metadata
    Show full item record
    Abstract
    Since the birth of digital social networks, management research focused upon the opportunities of social media marketing. A marketing campaign has the best success when it reaches the largest number of potential customers. It is, however, difficult to forecast in a precise way the number of contacts that you can reach with such an initiative. We propose a representation of social networks that captures both the probability of forecasting a message to different agents, and the time span during which the message is sent out. We study reachiability and coverage from the computational complexity viewpoint and show that they ...
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    Since the birth of digital social networks, management research focused upon the opportunities of social media marketing. A marketing campaign has the best success when it reaches the largest number of potential customers. It is, however, difficult to forecast in a precise way the number of contacts that you can reach with such an initiative. We propose a representation of social networks that captures both the probability of forecasting a message to different agents, and the time span during which the message is sent out. We study reachiability and coverage from the computational complexity viewpoint and show that they can be solved polynomially on deterministic machines.
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    Conference Title
    Smart Innovation, Systems and Technologies
    Volume
    96
    DOI
    https://doi.org/10.1007/978-3-319-92031-3_12
    Subject
    Artificial intelligence
    Publication URI
    http://hdl.handle.net/10072/384829
    Collection
    • Conference outputs

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