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On Using Temporal Networks to Analyze User Preferences Dynamics

  • Fabíola S. F. PereiraEmail author
  • Sandra de Amo
  • João Gama
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9956)

Abstract

User preferences are fairly dynamic, since users tend to exploit a wide range of information and modify their tastes accordingly over time. Existing models and formulations are too constrained to capture the complexity of this underlying phenomenon. In this paper, we investigate the interplay between user preferences and social networks over time. We propose to analyze user preferences dynamics with his/her social network modeled as a temporal network. First, we define a temporal preference model for reasoning with preferences. Then, we use evolving centralities from temporal networks to link with preferences dynamics. Our results indicate that modeling Twitter as a temporal network is more appropriated for analyzing user preferences dynamics than using just snapshots of static network.

Keywords

Temporal networks User preferences Evolving centralities 

Notes

Acknowledgments

This work was supported by the research project “TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact / NORTE-01-0145-FEDER-000020”, financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF) and by European Commission through the project MAESTRA (Grant number ICT-2013-612944). Fabiola Pereira is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalization - COMPETE 2020 Programme within project POCI-01-0145-FEDER-006961, and by National Funds through the FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) as part of project UID/EEA/50014/2013. This work was also supported by the Brazilian Research Agencies CAPES and CNPq.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Fabíola S. F. Pereira
    • 1
    Email author
  • Sandra de Amo
    • 1
  • João Gama
    • 2
  1. 1.Federal University of UberlândiaUberlândiaBrazil
  2. 2.LIAAD INESC TECUniversity of PortoPortoPortugal

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