Explorando a complementaridade entre estratégias para detecção de usuários influentes no Twitter - Neves, Alan; Vieira, Ramon; Mourão, Fernando; Rocha, Leonardo (Proceedings of the SBC Undergraduate Research Contest (CTIC-SBC), 2015)
The so-called influencers have an important role on the information diffusion in social media environments, since they might dictate peer-to-peer recommendation, impacting tasks such as brand evaluation, advertising, etc. Despite the growing number of works that identify influencers by exploiting distinct information, deciding on the best strategy for each domain is complex. In this work, we perform a quantitative study among some of the main strategies for identifying influencers. As main contributions, we highlight a better understanding about the selected strategies and a novel and effective meta-learning approach, based on PCA, that is able to combine linearly distinct strategies.