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020 _a9783030688400
024 7 _a10.1007/978-3-030-68840-0
_2doi
040 _aES-MaUEC
_bspa
_cES-MaUEC
_dES-MaUEC
050 4 _aQA76.9.A94
_b2021 EB
100 _aBeierle, Felix
_eautor
_0(orcid)0000-0003-2702-9893
_1https://orcid.org/0000-0003-2702-9893
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_9682055
245 1 0 _aIntegrating Psychoinformatics with Ubiquitous Social Networking :
_bAdvanced Mobile-Sensing Concepts and Applications
_cby Felix Beierle.
250 _aFirst edition 2021
264 1 _aCham
_bSpringer International Pulishing
_c2021
300 _a1 recurso en línea (XXIV, 196 páginas)
_b39 ilustraciones, 26 ilustraciones a color
336 _2rdacontent
_aTexto
_btxt
337 _2rdamedia
_aelectrónico
_bc
338 _2rdacarrier
_arecurso electrónico
_bcr
347 _aarchivo de texto
_bPDF
490 0 _aT-Labs Series in Telecommunication Services
_x2192-2810
490 0 _aIntelligent Technologies and Robotics (SpringerNature-42732)
490 0 _aIntelligent Technologies and Robotics (R0) (SpringerNature-43728)
505 0 _aChapter 1. Introduction -- Part I. Mobile Sensing and Personality -- Chapter 2. Overview -- Chapter 3. Related Work -- Chapter 4. TYDR - Track Your Daily Routine -- Chapter 5. Smartphone Usage Frequency and Duration in Relation to Personality Traits -- Chapter 6. Interim Conclusions for Part I: Privacy-aware Mobile Sensing in Psychoinformatics -- Part II. Mobile Sensing in Ubiquitous Social Networking -- Chapter 7. Overview -- Chapter 8. Related Work -- Chapter 9. SimCon - A Concept for Contact Recommendations -- Chapter 10. Similarity Estimation -- Chapter 11. MobRec - Mobile Platform for Decentralized Recommender Systems -- Chapter 12. GroupMusic - Recommender System for Groups -- Chapter 13. Interim Conclusions for Part II: Advancing Ubiquitous Social Networking Through Mobile Sensing -- Part III. Conclusions and Outlook -- Chapter 14. Conclusions -- Chapter 15. Outlook.
520 3 _aThis book deepens the understanding of people through smartphone data obtained via mobile sensing and applies psychological insights for social networking applications. The author first introduces TYDR, an application for researching smartphone data and user personality. A novel, structured privacy model for mobile sensing applications is developed and the obtained empirical results help researchers gauge what data they can expect users to share in daily-life studies. The new research findings, the concept of mobile sensing, and psychological insights about the formation and structure of real-life social networks are integrated into the field of social networking. Finally, for this novel integration, the author presents concepts, decentralized software architectures, and fully realized prototypes that recommend new contacts, media, and locations to individual users and groups of users. Provides a psychoinformatical research framework for mobile sensing and user personality; Includes an app, a privacy model, example studies, and empirical insights about study participants' willingness to share data; Introduces decentralized social networking concepts and applications based on psychological research results.
988 _aSpringer_Robotics_2021
650 7 _2embne
_9141180
_aProceso de datos
776 0 8 _iPrinted edition:
_z9783030688394
776 0 8 _iPrinted edition:
_z9783030688417
776 0 8 _iPrinted edition:
_z9783030688424
856 4 0 _uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-68840-0
_zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942 _2lcc
_cLE