Contextual Social Networking

The thesis centers around the multi-faceted research question of how contexts may be detected and derived that can be used for new context aware Social Networking services and for improving the usefulness of existing Social Networking services, giving rise to the notion of Contextual Social Networking. In a first foundational part, we characterize the closely related fields of Contextual-, Mobile-, and Decentralized Social Networking using different methods and focusing on different detailed aspects. A second part focuses on the question of how short-term and long-term social contexts as especially interesting forms of context for Social Networking may be derived. We focus on NLP based methods for the characterization of social relations as a typical form of long-term social contexts and on Mobile Social Signal Processing methods for deriving short-term social contexts on the basis of geometry of interaction and audio. We furthermore investigate, how personal social agents may combine such social context elements on various levels of abstraction. The third part discusses new and improved context aware Social Networking service concepts. We investigate special forms of awareness services, new forms of social information retrieval, social recommender systems, context aware privacy concepts and services and platforms supporting Open Innovation and creative processes. This version of the thesis does not contain the included publications because of copyrights of the journals etc. Contact in terms of the version with all included publications: Georg Groh, [email protected] zentrale Gegenstand der vorliegenden Arbeit ist die vielschichtige Frage, wie Kontexte detektiert und abgeleitet werden können, die dazu dienen können, neuartige kontextbewusste Social Networking Dienste zu schaffen und bestehende Dienste in ihrem Nutzwert zu verbessern. Die (noch nicht abgeschlossene) erfolgreiche Umsetzung dieses Programmes führt auf ein Konzept, das man als Contextual Social Networking bezeichnen kann. In einem grundlegenden ersten Teil werden die eng zusammenhängenden Gebiete Contextual Social Networking, Mobile Social Networking und Decentralized Social Networking mit verschiedenen Methoden und unter Fokussierung auf verschiedene Detail-Aspekte näher beleuchtet und in Zusammenhang gesetzt. Ein zweiter Teil behandelt die Frage, wie soziale Kurzzeit- und Langzeit-Kontexte als für das Social Networking besonders interessante Formen von Kontext gemessen und abgeleitet werden können. Ein Fokus liegt hierbei auf NLP Methoden zur Charakterisierung sozialer Beziehungen als einer typischen Form von sozialem Langzeit-Kontext. Ein weiterer Schwerpunkt liegt auf Methoden aus dem Mobile Social Signal Processing zur Ableitung sinnvoller sozialer Kurzzeit-Kontexte auf der Basis von Interaktionsgeometrien und Audio-Daten. Es wird ferner untersucht, wie persönliche soziale Agenten Kontext-Elemente verschiedener Abstraktionsgrade miteinander kombinieren können. Der dritte Teil behandelt neuartige und verbesserte Konzepte für kontextbewusste Social Networking Dienste. Es werden spezielle Formen von Awareness Diensten, neue Formen von sozialem Information Retrieval, Konzepte für kontextbewusstes Privacy Management und Dienste und Plattformen zur Unterstützung von Open Innovation und Kreativität untersucht und vorgestellt. Diese Version der Habilitationsschrift enthält die inkludierten Publikationen zurVermeidung von Copyright-Verletzungen auf Seiten der Journals u.a. nicht. Kontakt in Bezug auf die Version mit allen inkludierten Publikationen: Georg Groh, [email protected]

Mediating chance encounters through opportunistic social matching

Chance encounters, the unintended meeting between people unfamiliar with each other, serve as an important social lubricant helping people to create new social ties, such as making new friends or finding an activity, study or collaboration partner. Unfortunately, social barriers often prevent chance encounters in environments where people do not know each other and people have to rely on serendipity to meet or be introduced to interesting people around them. Little is known about the underlying dynamics of chance encounters and how systems could utilize contextual data to mediate chance encounters. This dissertation addresses this gap in research literature by exploring the design space of opportunistic social matching systems that aim to introduce relevant people to each other in the opportune moment and the opportune place in order to encourage face-to-face interaction. A theoretical framework of relational, social and personal context as predictors of encounter opportunities is proposed and validated through a mixed method approach using interviews, experience sampling and a field study of a design prototype. Key contributions of the field interview study (n=58) include novel context-aware social matching concepts such as: sociability of others as an indicator of opportune social context; activity involvement as an indicator of opportune personal context; and contextual rarity as an indicator of opportune relational context. The following study combining Experience Sampling Method (ESM) and participant interviews extends prior research on social matching by providing an empirical foundation for the design of opportunistic social matching systems. A generalized linear mixed model analysis (n=1781) shows that personal context (mood and busyness) together with the sociability of others nearby are the strongest predictors of people’s interest in a social match. Interview findings provide novel approaches on how to operationalize relational context based on social network rarity and discoverable rarity. Moreover, insights from this study highlight that additional meta-information about user interests is needed to operationalize relational context, such as users’ passion level for an interest and their skill levels for an activity. Based on these findings, the novel design concept of passive context-awareness for social matching is put forward. In the last study, Encount’r, an instantiation of an opportunistic social matching system, is designed and evaluated through a field study and participant interviews. A large-scale user profiling survey provides baseline rarity measures to operationalize relational context using rarity, passion levels, skills, needs, and offers. Findings show that attribute type, computed attribute rarity, self-reported passion levels for interest, and response time are associated with people’s interest in a match opportunity. Moreover, this study extends prior work by showing how the concept of passive context-awareness for opportunistic social matching is promising. Collectively, contributions of this work include a theoretical framework encompassing relational, social, and personal context; new innovative concepts to operationalize each of these aspects for opportunistic social matching; and field-tested design affordances for opportunistic social matching systems. This is important because opportunistic social matching systems can lead to new social ties and improved social capital