In this paper, we describe a novel data model for particular online business social networks such as Tripadvisor and Yelp: we also define a greedy influence maximization algorithm to determine the most influential users on the base of proper influence patterns. The result of such analysis is then combined with some economic data in order to propose a set of possible financial strategies for business objects. Finally, a case study and some preliminary and interesting results are presented for the Yelp dataset.
Influence Analysis in Business Social Media / Amato, Flora; Moscato, Vincenzo; Picariello, Antonio; Ponti, Giovanni; Sperlì, Giancarlo. - 1941:(2017), pp. 43-54. (Intervento presentato al convegno Second Workshop on MIning DAta for financial applicationS (MIDAS 2017) co-located with the 2017 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2017) tenutosi a Skopje, Macedonia nel September 18, 2017).
Influence Analysis in Business Social Media
Flora Amato;Vincenzo Moscato;Antonio Picariello;Giovanni Ponti;Giancarlo Sperlì
2017
Abstract
In this paper, we describe a novel data model for particular online business social networks such as Tripadvisor and Yelp: we also define a greedy influence maximization algorithm to determine the most influential users on the base of proper influence patterns. The result of such analysis is then combined with some economic data in order to propose a set of possible financial strategies for business objects. Finally, a case study and some preliminary and interesting results are presented for the Yelp dataset.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
