Authors:
Ramon Hermoso
1
and
Maria Fasli
2
Affiliations:
1
University of Zaragoza, Spain
;
2
University of Essex, United Kingdom
Keyword(s):
Artificial Societies, Social Networks, Innovation, Entry Point.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Distributed and Mobile Software Systems
;
Economic Agent Models
;
Enterprise Information Systems
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Model-Based Reasoning
;
Multi-Agent Systems
;
Software Engineering
;
Symbolic Systems
Abstract:
Social networks have grown massively in the last few years and have become a lot more than mere message
exchange platforms. Apart from serving purposes such as linking friends and family, job linking or news
feeding, their nearly pervasive nature and presence in day-to-day activities make them the biggest potential
market and access platform to hundreds of millions of customers ever built. Faced with such a complex
and challenging environment, we claim that introducing innovation in an efficient way in such networks is
of extreme importance. In this paper, we put forward a mechanism to select suitable entry points in the
network to introduce the innovation, so fostering its acceptance and enhancing its diffusion. To do this, we
use the underlying structure of the network as well as the influencing power some users exercise over others.
We present results of testing our approach with both a Facebook dataset and different examples of random
networks.