Using attractiveness model for actors ranking in social media networks

• Published in: Computational social networks 2017-01, Vol.4 (1), p.3-15, Article 3
• Main Authors: Qasem, Ziyaad, Jansen, Marc, Hecking, Tobias, Hoppe, H. Ulrich
• Format: Article
• Language: English
• Subjects: Communities; Computer simulation; Data-driven Science; Database Management; Digital media; Industrial and Production Engineering; Industrial Organization; Information dissemination; Mathematical Models of Cognitive Processes and Neural Networks; Mathematics; Mathematics and Statistics; Media Sociology; Modeling and Theory Building; Optimization; Seeds; Social networks; Special Issue of the 5th International Workshop on Complex Networks and Their Applications; Spreaders
• ISSN: 2197-4314; 2197-4314
• DOI: 10.1186/s40649-017-0040-8

Background Influential actors detection in social media such as Twitter or Facebook can play a major role in gathering opinions on particular topics, improving the marketing efficiency, predicting the trends, etc. Proposed methods This work aims to extend our formally defined T measure to present a new measure aiming to recognize the actor’s influence by the strength of attracting new important actors into a networked community. Therefore, we propose a model of the actor’s influence based on the attractiveness of the actor in relation to the number of other attractors with whom he/she has established connections over time. Results and conclusions Using an empirically collected social network for the underlying graph, we have applied the above-mentioned measure of influence in order to determine optimal seeds in a simulation of influence maximization. We study our extended measure in the context of information diffusion because this measure is based on a model of actors who attract others to be active members in a community. This corresponds to the idea of the IC simulation model which is used to identify the most important spreaders in a set of actors.