• DocumentCode
    253201
  • Title

    Strategic resource allocation for competitive influence in social networks

  • Author

    Masucci, Antonia Maria ; Silva, Alonso

  • Author_Institution
    INRIA Paris-Rocquencourt, Le Chesnay, France
  • fYear
    2014
  • fDate
    Sept. 30 2014-Oct. 3 2014
  • Firstpage
    951
  • Lastpage
    958
  • Abstract
    One of the main objectives of data mining is to help companies determine to which potential customers to market and how many resources to allocate to these potential customers. Most previous works on competitive influence in social networks focus on the first issue. In this work, our focus is on the second issue, i.e., we are interested on the competitive influence of marketing campaigns who need to simultaneously decide how many resources to allocate to their potential customers to advertise their products. Using results from game theory, we are able to completely characterize the optimal strategic resource allocation for the voter model of social networks and prove that the price of competition of this game is unbounded. This work is a step towards providing a solid foundation for marketing advertising in more general scenarios.
  • Keywords
    advertising data processing; data mining; game theory; resource allocation; social networking (online); competitive influence; data mining; game theory; marketing advertising; marketing campaigns; optimal strategic resource allocation; social networks; voter model; Games; Joints; Nash equilibrium; Resource management; Social network services; Vectors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication, Control, and Computing (Allerton), 2014 52nd Annual Allerton Conference on
  • Conference_Location
    Monticello, IL
  • Type

    conf

  • DOI
    10.1109/ALLERTON.2014.7028557
  • Filename
    7028557