Published August 28, 2018
| Version v1
Conference paper
A Generalized Fractional Program for Maximizing Content Popularity in Online Social Networks
- Others:
- Indian Institute of Science [Bangalore] (IISc Bangalore)
- Laboratoire Informatique d'Avignon (LIA) ; Avignon Université (AU)-Centre d'Enseignement et de Recherche en Informatique - CERI
- Network Engineering and Operations (NEO ) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
- Laboratory of Information, Network and Communication Sciences (LINCS) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut Mines-Télécom [Paris] (IMT)-Sorbonne Université (SU)
- COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)
- Laboratoire Biens, Normes, Contrats (LBNC) ; Avignon Université (AU)
Description
In this paper, we consider a "generalized" fractional program in order to solve a popularity optimization problem in which a source of contents controls the topics of her contents and the rate with which posts are sent to a time line. The objective of the source is to maximize its overall popularity in an Online Social Network (OSN). We propose an efficient algorithm that converges to the optimal solution of the Popularity maximization problem.
Abstract
International audience
Additional details
- URL
- https://hal.inria.fr/hal-01907060
- URN
- urn:oai:HAL:hal-01907060v1
- Origin repository
- UNICA