Authors:
Ermelinda Oro
;
Clara Pizzuti
and
Massimo Ruffolo
Affiliation:
National Research Council (CNR), Italy
Keyword(s):
Social Network, Social Media, Twitter, Influential User, Twitter Influencer, Product Perception, Social Network Analysis, Multilayer Networks, Multilinear Algebra, Tensor Decomposition.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Electronic Commerce
;
Enterprise Information Systems
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Society, e-Business and e-Government
;
Software Agents and Internet Computing
;
Symbolic Systems
;
User Profiling and Recommender Systems
;
Web 2.0 and Social Networking Controls
;
Web Information Systems and Technologies
Abstract:
The massive amount of information posted by twitterers is attracting growing interest because of the several applications fields it can be utilized, such as, for instance, e-commerce. In fact, tweets enable users to express opinions about products and to influence other users. Thus, the identification of social network key influencers with their products perception and preferences is crucial to enable marketers to apply effective techniques of viral marketing and recommendation. In this paper, we propose a methodology, based on multilinear algebra, that combines topological and contextual information to identify the most influential twitterers of specific topics or products along with their perceptions and opinions about them. Experiments on a real use case regarding smartphones show the ability of the proposed methodology to find users that are authoritative in the social network in expressing their views about products and to identify the most relevant products for these users, alo
ng with the opinions they express.
(More)