Title :
Strategic resource allocation for competitive influence in social networks
Author :
Masucci, Antonia Maria ; Silva, Alonso
Author_Institution :
INRIA Paris-Rocquencourt, Le Chesnay, France
fDate :
Sept. 30 2014-Oct. 3 2014
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;
Conference_Titel :
Communication, Control, and Computing (Allerton), 2014 52nd Annual Allerton Conference on
Conference_Location :
Monticello, IL
DOI :
10.1109/ALLERTON.2014.7028557