Details
Integrating Psychoinformatics with Ubiquitous Social Networking
Advanced Mobile-Sensing Concepts and ApplicationsT-Labs Series in Telecommunication Services
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96,29 € |
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| Verlag: | Springer |
| Format: | |
| Veröffentl.: | 23.04.2021 |
| ISBN/EAN: | 9783030688400 |
| Sprache: | englisch |
Dieses eBook enthält ein Wasserzeichen.
Beschreibungen
This 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.<br><p></p>
Chapter 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.<p></p>
<p>Felix Beierle received an M.A. degree in media studies and American studies from the University of Marburg in 2009, an M.Sc. degree in computer science from the University of Hagen in 2014, and a Ph.D. in computer science from Technische Universität Berlin in 2020. His research interests include ubiquitous computing, mHealth, social networking, and recommender systems. He currently is a postdoc with the Service-centric Networking group at Technische Universität Berlin and Telekom Innovation Laboratories in Berlin, Germany.<b></b></p><p></p>
<div>This 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.<br></div><div><p></p><ul><li>Provides a psychoinformatical research framework for mobile sensingand user personality;</li><li>Includes an app, a privacy model, example studies, and empirical insights about study participants’ willingness to share data;</li><li>Introduces decentralized social networking concepts and applications based on psychological research results.</li></ul><p></p>
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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
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