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Foundations of Trust: Contextualising Trust in Social Clouds Simon Caton,∗ Christoph Dukat,† Tilo Grenz,† Christian Haas,∗ Michaela Pfadenhauer,† and Christof Weinhardt∗ ∗ Karlsruhe
Services Research Institute / † Institute for Sociology, Karlsruhe Institute of Technology, Germany {simon.caton, christoph.dukat, tilo.grenz, ch.haas, michaela.pfadenhauer, weinhardt}@kit.edu
Abstract—In this paper, we lay the foundations for a contextualisation of trust, the role it plays, and its different layers within the context of a novel paradigm: Social Cloud Computing. In a Social Cloud, trust plays a vital role as a collaboration enabler. However, trust is not trivial to define, observe, represent and analyse as precursors to understand exactly what role it plays in the enablement of collaboration. We do this through the definition of structure of a Social Cloud as a sequence of social and cognitive processes. We then survey research from the domains of computer science, economics and sociology that consider trust in online communities and exchange scenarios to illustrate the complexity of modelling trust in our scenario. Finally, we define trust within the context of a Social Cloud and identify the core components of trust to facilitate its understanding.
I. I NTRODUCTION The ever increasing pervasiveness of Social Network Platforms has profoundly changed the way that we communicate and interact today. They allow us to interact within virtual platforms, establish and engage in virtual communities, as well as represent, document and explore our inter-personal relationships in a digital manner. Their widespread uptake has meant that our electronic relationships are beginning to be intertwined with their real world counterparts, and in some cases are indistinguishable. Consequently, a large portion of social interaction now takes place via social network platforms. In parallel, the rise of distributed computing and service paradigms like Cloud Computing have made the acquisition and consumption of Internet services more common. Yet, studies have shown that issues such as trust, security, anonymity and sometimes reliability are significant obstacles for these paradigms. As an alternative, we defined the concept of a Social Cloud in [1], [2] to build upon the today’s prolific use of social network platforms, users’ increasing technical adeptness thanks to web and Internet science, and that users’ locally available capabilities and resources are dramatically increasing. The latter means that many Internet users have resource endowments that studies have shown to be 60-95% idle [3]–[5]. The volunteering computing paradigm has also demonstrated that users will make idle resources available for “good uses” either altruistically or without a directly expected utility. Consider that an average Facebook user has 190 friends,1 and our vision of a Social Cloud: a resource 1 http://tinyurl.com/fb-anatomy
– last accessed May 2012
and service sharing framework that utilizes relationships established between members of a social network [2] emerges. Social Clouds provide an environment in which (new) provisioning and sharing scenarios can be established based upon implicit levels of trust that transcend from the interpersonal relationships digitally encoded within social network platforms. The vision of a Social Cloud is motivated by the need of individuals or groups for specific resources or capabilities that could be made available by connected peers and peer groups. In simple words, Social Clouds use social networks as mechanisms for efficient collaboration, as users leverage their existing networks to share capabilities and resources. Resources are not necessarily only computational resources, but can be any electronically exchangeable service, including human resources, skills and capabilities. This definition contains a key assumption: using trust as a vehicle for exchange implies that leveraging existing relationships are better or more efficient than anonymous-based exchanges. It also does not reflect the type of trusted relationship needed for a successful exchange. The concept of trust therefore requires an analytical understanding as a concept of social action and context. Therefore, in this paper we examine the context of trust and its key aspects for online collaboration. We address the challenge of defining and understanding trust, such that it can be leveraged as an exchange enabler for a Social Cloud, specified and investigated experimentally. This paper is organised as follows: section II, describes the structure of a Social Cloud. Section III, surveys trust in collaboration contexts. Section IV, discusses a trust definition for a Social Cloud. Section V, summarises the paper. II. S OCIAL C LOUD PARTICIPATION AND I NTERACTION To help define the context of a Social Cloud and the roles of trust, we briefly describe the structure of a Social Cloud as a sequence of social and cognitive processes (Fig. 1). We present three stages: Prior Expections, Social Interchange and Completion. Their cyclic dependencies demonstrate the evolutionary nature of interactions within a Social Cloud, and highlight how past interactions influence user expectations. A. Prior Expectations The ex-ante stage prior expectations captures why a user would consider using or joining a Social Cloud, how they
Fig. 1.
Social Cloud Exchange Structure
change. We differentiate between formal and informal aspects, where formal aspects define collaboration as an economic system and informal define the social and context specific structures that help facilitate exchange as a socially-driven process. In general, the core aspects of this stage are focused around: the identification and allocation of demand and supply using socio-economic mechanisms; messaging mechanisms (for communication and coordination), or other mediums that can be compared to social network platforms; and the provisioning and delivery of exchanged artefact(s). C. Completion
envisage their benefit of its use and the contribution they can make. We identify two aspects that shape the expectations of a user: their motivation, and the existence of demand and supply. Motivation is expressed via the following aspects: 1) expected outcome of the social exchange, 2) social context and 3) individual as well as network history. The outcome of an exchange captures several elements of providing as well as consuming resources. This includes aspects like a gain in utility, fulfillment of a goal, completion of a task, and feeling of inclusion or usefulness. These actions incur a sense of belonging or togetherness via participation in a Social Cloud. Yet we note, that specific incentive schemes (see [6]) may also be drivers of participation. The social context captures specific properties of the Social Cloud and its users: relationship types (e.g. family, close friend, acquaintance, colleague etc.); specific properties of the social graph (e.g. centrality, and conntectivity); and finally the implicit levels of trust between a user and their friends. Trust plays a crucial role and contains several frames of reference: 1) trust as an intrinsic (subjective) attribute of an inter-personal social relation, i.e. trust as a basic foundation of social actions; 2) trust in the competence of an individual to be able to deliver a given resource or capability, i.e. a belief in the self-awareness and personal re-evaluation of self-efficacy undertaken by an individual as a precursor to partaking in a Social Cloud; 3) trust in an individual to deliver, i.e. keep their promises, adhere to any (informal) agreements etc. The final aspect of user motivation is the observation of interaction history, which is described in the completion stage. Supply is the circumstantial availability of a useful resource or capability in a Social Cloud. In other words, excess driven demand - where the need of an individual is satisfied by the circumstantial offering of excess resources or capabilities by their peers. Demand is the observation of individual needs that encourage users to provide to their peers, i.e. it is demandinduced social capital - where the need of one or more users in the Social Cloud compels other users to make their excess resources or capabilities available as a form of social capital. B. Social Interchange Social Interchange entails the facilitatation of collaboration and exchange between socially-connected peers. Many methods exist for the construction and representation of this stage, which we do not elaborate on here. Instead, we illustrate the core components of a platform for collaborative social ex-
The ex-post stage Completion addresses the processes and actions that finalise an exchange, and contains three key components: feedback, recommendation and archiving. Completion provides an element of closure to a social exchange and potentially results in a positive or negative change to the relationships of users, as completion does not imply success. Feedback is the social dissemination of an exchange as an exercise in reflection and communication via two modes: 1) local feedback, i.e. between users (potentially privately), and 2) public feedback via social channels like notifications, newsfeeds, and Facebook’s Timeline. Feedback includes: the benefit to consumer, potentially a reward given to the provider or a message of thanks. For a Social Cloud, feedback demonstrates usefulness, is a means to attract users, encourage participation, and demonstrates the existence of trust. Recommendation is the suggestion of an action after a positive and negative exchange outcome, i.e. whether to reward or sanction a user. This process is heavily dependent on the social context of a collaboration. In other scenarios, such actions would be defined in service level agreements. Yet, this is difficult to argue in the case of a Social Cloud, as rigidly engineered forms of interaction completion cannot consider the intricate details of a social context. It may also not be possible to determine if an exchange was successful or not, without additional information supplied by users. Interaction Archiving is the documentation of collaboration processes. Although a simple task, it is critical for the understanding of trust, its evolution between users and its social context. Archives act as repositories for determining collaboration performance and social cohesion (often the result of interaction history) as a result of specific inter-individual exchanges based on positive expectation (trust). III. S URVEY OF R ESEARCH INTO T RUST Trust in the context of a Social Cloud requires an interdisciplinary understanding. In this section, we present an interdisciplinary survey as a basis for discussion. We select Computer Science with a focus on the technical implementation of trust; economics with a focus on how trust effects the economic behaviour of a system’s users, the system itself as well as economic situations where trust plays a crucial role; and Sociology with a focus on the theoretical basis for the explaination of context (e.g. history, setting, and expectations) and fundamental characterisation of (social) exchange.
A. Trust in Information and Computer Science With the advent of electronic platforms where users can interact with each other, such as e-commerce or P2P platforms, is has become necessary to define and implement computational notions of trust. In order for interactions to occur in these types of platforms, the exchange between users has to be facilitated by technical features that address and try to alleviate the trust issue in such systems. Building on research from other disciplines, computer and information science has focused on applying these principles to technical systems. Examples are reputation systems to create a certain level of trust (e.g. eBay, and P2P networks), sharing platforms targeted at a certain user group (e.g. MyExperiment), algorithms to calculate trust scores between users, and approaches that leverage social networks as a basic premise for collaborative exchange. Today, investigations into adopting social network structures for different types of collaboration are in their infancy. Key examples are: community and scientific portals like PolarGRID [7] and ASPEN [8]; social storage systems like Friendstore [9], and omemo.com; the sharing of networks and infrastructure (e.g. fon.com), the distribution of insurance policies amongst social peers (friendsurance.de) and where social networks emerge due via collaboration, e.g. [10], [11]. In such cases, the social network (and therefore “trusted” context) emerges artificially as a consequence of use or the social network platform is used to perform mundane tasks like user authentication, and messaging. In both cases, it is impossible to try and understand the context of trust behind such approaches. Alternatively, the approach exists outside of the social network platform. In such cases, no consideration is made on how the digital relationship representation can be leveraged detaching the notion of trust as a collaboration vechicle. The key exception here is Friendsurance, which although it doesn’t explicitly harness the social graph, it leverages existing relationships between friends to enable friend- and community-based insurance contracts. Here, small insurance claims are covered by friends or the community, and larger ones are given to insurance company resulting in lower insurance fees. Trust in this context, however, is somewhat overshadowed by the system’s legal (i.e. contractual) context. Three notable approaches to sharing resources in social contexts are MyExperiment.org [10], nanoHUB.org [11] and Social Volunteer Computing [12]. MyExperiment is a platform where users can provide and work on workflows for scientific processes which facilitates the sharing and dissemination of common workflows. nanoHUB lets users share (teaching and research) resources in the field of nanotechnology and uses a simple virtual currency as participation incentives to users. Social Volunteer Computing is intended as the next generation of Volunteer Computing where users have underlying social relationships. However, each of these concepts are specialized to certain types of resources, do not extend beyond their virtual context, or do not consider actual sharing due to a missing bilateral focus. Hence, they lack the setting to investigate the role of trust and leverage it in exchanges.
In the integration of trust in electronic systems, several reputation mechanisms that measure, represent or use trust scores have been proposed (e.g. [13]–[16]). Their aim is to calculate a measure of trust based on feedback of users, previous interactions, and other factors. Social Regret [14] is an augmented reputation system that leverages social relationships and social network analysis. It considers private and forms of community reputation (such as neighborhood reputation) and takes into account the reliability of reputation information. EigenTrust [15] is a means to decrease the number of fake files in P2P sharing networks. Through the calculation of a global trust score for each peer, and with the approach that users should select their download peer based on this global trust value, the authors show that the number of fake/corrupt files in the network significantly decreases. Trust in this context can be seen as selecting a download peer without receiving fake files. PeerTrust [16] aims to calculate the trustworthiness of peers in a P2P exchange scenario, taking into account aspects such as feedback from other users and its credibility, number of transactions and even the context of transactions. It defines a trust metric that aggregates the individual trust measures to a single number. PowerTrust [13] leverages power-law distributions of user feedback and a trust network to improve the accuracy and scalability of a reputation system. All of these systems focus on the measurement and implementation of trust scores, taking the existence and influence of trust as a given or don’t consider social contexts. B. Trust in Economics Where computer and information science focuses on the technical implementation of trust in (electronic) systems, economics focuses on how trust effects the behaviour of market participants and what role trust plays in the functioning of a market itself. Trust is seen as an important facilitator of markets (see e.g. [17]), as there is the risk of opportunistic default in many market settings (i.e. sellers do not ship after payment, or buyers do not pay for goods). Or, as [18] puts it: “Virtually every commercial transaction has within itself an element of trust, certainly any transaction conducted over a period of time. It can be plausibly argued that much of the economic backwardness in the world can be explained by the lack of mutual confidence.” Kozinets’ [19] research on “virtual togetherness” showed that exchange and cooperation changes with the developmental progression of individual member participation and interpersonal exchange, which is one of the basic assumptions of trust from a sociological perspective. The economic notions of trust, however, mainly focus on the effect of trust relationships upon economic outcomes. Among the first, the existence of Social Networks and their interplay on economic processes has been studied by Granovetter [17], [20] who assessed the effect of social networks on job information distribution. He found that the dissemination of job information depends on the structure of the underlying network, and that the “weak” ties between almost separate, clustered groups play important roles in the dissemination of information among these groups. More recently, [21] study the
influence of social links and trust on business transactions such as auctions. In particular, they study an online auction platform which includes social network capabilities. They find that users actually make use of their social network for business purposes or transactions, which benefits the users via higher user satisfaction rates. Furthermore, trust in pure business partners decays faster with the path length between two users, compared to trust between users in the social network. The effect of trust on economic outcomes has also been subject to many game theoretical studies, mainly in the form of the Trust game and the notion of reciprocity [22]. In the Trust game, which can be seen as a study of reciprocity itself, one player decides if and how much money to send to the second player, in which case the second player receives a multiple of the amount sent. In the next step, the second player can appreciate this gesture by sending a percentage back in return. Although the standard self-interest hypothesis postulates an equilibrium where no money is sent to the second player, a significant fraction of first players exhibit trust by sending money without knowing if they will get something in return. Based on these results, economic models of trust in the sense of reciprocal actions have been proposed in [23]. Yet, the notion of trust that is considered in these approaches does not consider specific relationships or social contexts. Economists have also made efforts to incorporate trust (and its effects) in their models. For example, [24] describes trust for economic cooperation, addressing how trust affects economic outcomes and discusses how trust can be measured. Another approach is the consideration of social or other-regarding preferences [23], [25], [26]. The aim of this area of economics is the explanation of empirical and laboratory findings where users do not act according to traditional economic assumptions such as Rational Choice. For example, in a Trust game, economic theory under the assumption of fully rational actors, predicts that nothing is shared. In contrast, the significant amount share in experiments is an indication that people place some sort of trust in their (unknown) counterpart. This fact is explained by several authors through different explanations, where reciprocal behavior and conditional cooperation are the concepts applied by most authors. The problem with some of the earlier experiments is that sometimes the concepts of other-regarding preferences are intertwined with trust and reciprocity, and it cannot be clearly inferred from experimental results where one of the factors truly is significant. To alleviate this issue, [27] ran experiments to specifically study the influence of trust vs. reciprocity in settings where other-regarding preferences play a role. The results show that all three aspects have a significant effect on the behaviour of participants, i.e. that they are different but equally significant factors. C. Trust in Sociology In sociology the phenomenon “trust” is mainly considered as a form of calculated risk taking corresponding to specific decision situations in social interactions. This understanding of trust can be found especially in rational choice [28] and systems theory [29]. Beyond this, trust is a crucial aspect
in the sociological discussion of modernization processes, where we can observe the diminishing of traditional “familiar” structures, changes in the relations of nearness and distance as well as increasing differentiations (e.g. diversification of expert knowledge) and technological forthcomings. Due to such developments and their corresponding risks, an increasing demand of trust, especially system trust, and the role of institutionalization processes to facilitate trust are identified [30]. However, an integrated socio-theoretical conceptualization that captures the complete phenomenon of trust is missing [31]. From a phenomenologically oriented sociology of knowledge perspective, Endress [32] tried to fill the gap by offering three levels of trust to tackle the limited view on trust he called reflexive trust that describes a “cognitive modus and strategic resource” and refers to the understanding of trust especially in rational choice theory. Endress stressed the importance of the aspect of “familiarity” (of knowledge) as a fundamental resource for trust. Based on this, he added two further levels of trust: “operational trust” and “habitual trust” which address the fundamental social theoretical prerequisite of the existence and the development of trust and distrust based on insights from ethnomethodological [33], phenomenological [34] and institutional [35] approaches that correspond to the actions of people in everyday life. “Operational trust” is defined as a “constitutive mode of trust”: a non-thematic elemental precondition of human action, which represents an implicitly unquestioned standpoint in the life-world [34], or “background expectation” according to [35]. Although it is hardly operationable, this level has to be kept in mind as a fundamental social theoretical dimension when dealing with the constitution of trust. The notion “habitual trust” is a “pragmatically effective fundament of routine and the product of interaction”. Upon this basis, we follow Endress’ definition of trust according to Lewis and Weigert [36]: Trust has to be considered as an (explicit or implicit) reciprocal orientation of at least two actors, which rests on the (explicit or implicit) common shared understanding of situation and which comes to expression in resulting structural behaviours and actions [37]. Besides the theoretical foundation of the complex concept of trust not much fundamental empirical research specifically on trust within modern social network sites like Facebook has been undertaken. Such networks have to be regarded as the context in which trust relationships are systematically embedded. Research on social networks mostly focuses on the (transforming) quality of friendship or traditional relationship types for which trust is an implicit but fundamental category [38]. Relationships and relationship practices have to be understood as socio-historical products that are interrelated with societal reflections, images and conventions on friendship [39]. Today, a significant degree are inscribed in social network infrastructures [38]. In contradiction to the 1990s notions of social isolation, early studies on Facebook already show strong empirical evidence that networking people tend to a social homogeneity [40] which even resulted in social processes of differentiation and separation of other groups [41]. For the individual concept of close relationships (in particular
friendship) a significant dynamism is described in later studies which is seen as a consequence of the shift from static relationship concepts to the instable practices (e.g. status updates, information posts, and a continual observation of others etc.), which Turkle [42] calls friended instead of a friend. For questions on trust in such networks and together with the ongoing empirical findings of homogeneity, it has been discussed if the (theoretical) notion of trust as an interactional and proved product has to be extended to a common goal of maintaining established networks [43]. It was Granovetter who already mentioned the impact of the quality of relationships on trust [44] (see also [45]). According to Granovetter’s idea it is necessary to consider the strength of relationships [20], the specific relationship dimensions [46] and concepts of internet ties [47] as well as the different roles they play for exchange processes in social networks and the usage of social capital [48]. Behind this background in empirical research it is necessary to regard both the level of reflexive and habitual trust as well as connect them with the dynamic qualities of different relationships. D. Summary We have surveyed many concepts of trust in computer and information science, economics and sociology. Yet, none proves sufficient for a fully rounded trust model that is fitting for a Social Cloud. Research from computer and information science focuses on the technical implementation of trust in electronic systems, but lacks the theoretical depth to understand trust. Instead, (often uninformed) models of trust are architected as a basis for decision making. Economics studies the effect of trust on economic outcomes, taking aspects such as the existence of trust as a given. This provides a premise to understand how trust can be leveraged under certain economic assumptions, but not how trust can be understood as a driver for exchange. Sociology studies the fundamentals of trust and investigates aspects such as the evolution of trust over time, its provenance and provides an contextualised understanding of trust as a multi-facteted social process. However, this is without any consideration of the technical context of trust for an online community, or its inclusion in exchanges. IV. I DENTIFYING T RUST FOR A S OCIAL C LOUD The realisation of a Social Cloud requires the design and implementation of a social middleware and trust models that combine the insights and overcome the shortcomings from three perspectives: computer science with a focus on the implementation of trust models for a Social Cloud; economics with a focus on an economic system for interpersonal exchange via trusted relationships; and sociology as bringing the fundamentals for the understanding of trust. This requires the underlying and shared understanding of trust as based on reciprocal implicit/explicit expectations according to different roles (consumer, provider) in diverse exchange contexts between social peers. Under consideration of a shared and interdisciplinary understanding of trust, we formulate a
preliminary definition of trust within the context of a Social Cloud as follows: Trust is a positive expectation or assumption on future outcomes that results from proven contextualised personal interaction-histories corresponding to conventional relationship types and can be leveraged by formal and informal rules and conventions within a Social Cloud to facilitate as well as influence the scope of collaborative exchange. Trust is a complex construct in which the past (events and experiences) and the future (plural expectations) are interwoven. In regard to future aspects, trust has to be considered as a multidimensional category, i.e. an attitude of plural expectations including competence, integrity and fairness as attributes of the trusted person (see [49] who raised the idea of multidimensional trust for eBay). This definition has many implications and demands the precise explaination of its fundamental aspects (especially the notions of proven and context) for a better understanding. Human beings always meet in a social context like family, organisationa or communities. People have encounters in interaction histories with each other within such contexts. The experiences which are made in these contexts function as implicit or explicit orientations for their future actions and exchanges with others. Above all, institutionalized formal and informal norms (e.g. reciprocity), which are not universal but interpreted in different social contexts, affect the constitution of trust and the formation of possible interactions. Proven means that ongoing interactions of at least two people are based on positive experiences with each other in the past. As a result, future encounters may become more and more unquestionable. In contrast, for example if one meets a person one time and one was disappointed by that person in this situation, then there might be a level of suspicion on the next encounter or decision to collaborate with this person. The contextualisation of encounters and in line with that of trust as a possible result of positive experiences within encounters has also to be considered in online contexts where encounters are taking place not directly (face-to-face) but indirectly, i.e. via technical (social) media. Here encounters and relationships are socio-technical-embedded. Accordingly, in the context of a Social Cloud computing environment, based on a social network, beside different kinds of technical mediated relationships, the inherent algorithms and its components are to be set in account for the constitution of trust. V. S UMMARY AND F UTURE W ORK We have presented trust as a key element for a Social Cloud and argued that we need a thorough understanding of trust and the role it plays. To address this issue, we presented the key stages of interaction in a Social Cloud as a frame of reference for trust as an enabler of collaboration. We then surveyed trust in collaboration and exchange for online communities and argued that trust in the context of socialnetwork based collaboration cannot currently be measured, represented or fully understood. Finally, we defined trust for a Social Cloud and articulated its key aspects. As future work we
will implement a socio-economic/socio-technical trust model for a Social Cloud to facilitate empirical studies that can quantify the extent of trust as collaboration enabler. R EFERENCES [1] Kyle Chard, Simon Caton, Omer Rana, and Kris Bubendorfer. Social Cloud : Cloud Computing in Social Networks. In 2010 IEEE 3rd International Conference on Cloud Computing (CLOUD), pages 99– 106, 2010. [2] Kyle Chard, Kris Bubendorfer, Simon Caton, and Omer Rana. Social Cloud Computing: A Vision for Socially Motivated Resource Sharing. IEEE Transactions on Services Computing, 99(PrePrints):1, 2011. [3] F. Douglis and J. Ousterhout. Transparent process migration: Design alternatives and the sprite implementation. Software Practice & Experience, Vol. 21, No. 8:757–785, 1991. [4] Matt W. Mutka. Estimating capacity for sharing in a privately owned workstation environment. IEEE Transactions on Software Engineering, Vol. 18, No. 4:319–328, 1992. [5] A. Acharya et al. The utility of exploiting idle workstations for parallel computation. In Proceedings of ACM International Conference on Measurement and Modelling of Computer Systems (SIGMETRICS 97), 1997. [6] C. Haas, S. Caton, and C. Weinhardt. Engineering incentives in social clouds. In Proceedings of the 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pages 572–575, 2011. [7] Zhenhua Guo, Raminderjeet Singh, and Marlon Pierce. Building the polargrid portal using web 2.0 and opensocial. In Proceedings of the 5th Grid Computing Environments Workshop (GCE ’09), pages 1–8, New York, NY, USA, 2009. ACM. [8] Roger Curry, Cameron Kiddle, Nayden Markatchev, Rob Simmonds, Tingxi Tan, Martin Arlitt, and Bruce Walker. Facebook Meets the Virtualized Enterprise. In Proceedings of the 12th International IEEE Enterprise Distributed Object Computing Conference (EDOC ’08), pages 286–292, Washington, DC, USA, 2008. IEEE Computer Society. [9] Dinh Nguyen Tran, Frank Chiang, and Jinyang Li. Friendstore: Cooperative online backup using trusted nodes. In Proceedings of the 1st International Workshop on Social Network Systems (SocialNet’08), Glasgow, Scotland, 2008. [10] David De Roure, Carole Goble, and Robert Stevens. The design and realisation of the myexperiment virtual research environment for social sharing of workflows. Future Generation Computer Systems, 25(5):561– 567, 2009. [11] Gerhard Klimeck, Michael McLennan, Sean P. Brophy, George B. Adams, and Mark S. Lundstrom. nanoHUB.org: Advancing Education and Research in Nanotechnology. Computing in Science and Engineering, 10:17–23, 2008. [12] Adam McMahon and Victor Milenkovic. Social volunteer computing. Journal on Systemics, Cybernetics and Informatics (JSCI), Volume 9(4):34 – 38, 2011. [13] Runfang Zhou and Kai Hwang. Powertrust: A robust and scalable reputation system for trusted peer-to-peer computing. IEEE Transactions on Parallel and Distributed Systems, pages 460–473, 2007. [14] Jordi Sabater and Carles Sierra. Social ReGreT, A reputation model based on social relations. SIGecom Exchanges, pages 44–56, 2002. [15] Sepandar D. Kamvar, Mario T. Schlosser, and Hector Garcia-molina. The Eigen-Trust Algorithm for Reputation Management in P2P Networks. In Proceedings of the 12th International World Wide Web Conference, Budapest, Hungary, 2003. [16] Li Xiong and Ling Liu. Peertrust: Supporting reputation-based trust for peer-to-peer electronic communities. IEEE Transactions On Knowledge and Data Engineering, pages 843–857, 2004. [17] Mark Granovetter. The Impact of Social Structure on Economic Outcomes. Journal of Economic Perspectives, 19(1):33–50, 2005. [18] Kenneth J. Arrow. Gifts and exchanges. Philosophy and Public Affairs, 1(4):343–362, 1972. [19] Robert V. Kozinets. E-Tribalized Marketing? The Strategic Implications of Virtual Communities of Consumption. 17(3):252–264, 1999. [20] M. S. Granovetter. The strength of weak ties. The American Journal of Sociology, 78(6):1360–1380, 1973. [21] Gayatri Swamynathan, Christo Wilson, Bryce Boe, Kevin Almeroth, and Ben Y. Zhao. Do social networks improve e-commerce?: a study on social marketplaces. In Proceedings of the first workshop on Online social networks, WOSN ’08, pages 1–6, New York, NY, USA, 2008.
[22] Joyce Berg, John Dickhaut, and Kevin McCabe. Trust, Reciprocity, and Social History. Games and Economic Behavior, 10(1):122–142, 1995. [23] Ernst Fehr and Klaus M. Schmidt. Chapter 8 The Economics of Fairness, Reciprocity and Altruism - Experimental Evidence and New Theories, volume 1 of Handbook on the Economics of Giving, Reciprocity and Altruism, pages 615–691. Elsevier, 2006. [24] Robert H.J. Mosch. The economic effects of trust. Theory and empirical evidence. PhD thesis, Tinbergen Institute, 2004. [25] G.E. Bolton and Axel Ockenfels. ERC: A theory of equity, reciprocity, and competition. The American Economic Review, 90(1):166–193, 2000. [26] Armin Falk and Urs Fischbacher. A theory of reciprocity. Games and Economic Behavior, 54(2):293 – 315, 2006. [27] James C. Cox. How to identify trust and reciprocity. Games and Economic Behavior, 46(2):260 – 281, 2004. [28] James S Coleman. Foundations of Social Theory, volume 69. Harvard University Press, 1990. [29] Niklas Luhmann. Vertrautheit, Zuversicht, Vertrauen. Probleme und Alternativen. In Martin Hartmann and Claus Offe, editors, Vertrauen. Die Grundlage des sozialen Zusammenhalts, pages 143–160. 2001. [30] A. Giddens. Konsequenzen der Moderne. Suhrkamp-Taschenbuch Wissenschaft. Suhrkamp, 1997. [31] Martin Endress. Vertrauen - soziologische perspektiven. In Matthias Maring, editor, Vertrauen - zwischen sozialem Kitt und der Senkung von Transaktionskosten. KIT Scientific Publishing, Karlsruhe, 2010. [32] M. Endress. Trust and the dialectic of the familiar and the unfamiliar within the life-world. In Interaction and Everyday Life. Phenomenological and Ethnomethodological Essay in Honor of George Psathas. Lanham a.o.: Lexington Books, forthcoming. [33] H. Garfinkel. A conception of, and experiments with, trust’ as a condition of stable concerted actions. In O. J. Harvey, editor, Motivation and Social Interaction, pages 187–238. New York, 1963. [34] Alfred Schtz and Thomas Luckmann. Strukturen der Lebenswelt. UVK Verlagsgesellschaft, 2003. [35] Lynne G Zucker. Production of trust: Institutional sources of economic structure, 1840-1920. Research In Organizational Behavior, 8:53–111, 1986. [36] J. David Lewis and Andrew Weigert. Trust as a social reality. Social Forces, 63(4):pp. 967–985, 1985. [37] Martin Endress. Vertrauen. Bielefeld: transcript Verl., 2002. [38] Ralf Adelmann. Von der freundschaft in facebook. mediale politiken sozialer beziehungen in social network sites. In Generation Facebook. ber das Leben im Social Net. Leistert, O. / Roehle, T., Bielefeld, 2011. [39] J. Derrida and S. Lorenzer. Politik der Freundschaft. Suhrkamp Taschenbuch Wissenschaft. Suhrkamp, 2002. [40] Nicole B. Ellison, Charles Steinfield, and Cliff Lampe. The Benefits of Facebook Friends: Social Capital and College Students’ Use of Online Social Network Sites. Journal of Computer-Mediated Communication, 12(4):1143–1168, July 2007. [41] Danah Boyd. Friendship. In Mizuko Ito, Sonja Baumer, and Matteo Bittanti (Eds.), editors, Hanging Out, Messing Around, Geeking Out: Living and Learning with New Media, pages 79–115. MIT Press, 2010. [42] Sherry Turkle. Alone Together: Why We Expect More from Technology and Less from Each Other. Basic Books, Inc., NY, USA, 2011. [43] Andreas Wittel. Auf dem weg zu einer netzwerk-sozialitt. In A. Hepp, F. Krotz, S. Moores, and C. Winter, editors, Konnektivitt, Netzwerk und Fluss, pages 163–188. VS Verlag fr Soz.wiss., 2006. [44] Mark Granovetter. Economic action and social structure: The problem of embeddedness. American Journal of Sociology, 91(3):481–510, 1985. [45] Henning Nuissl. Bausteine des vertrauens - eine begriffsanalyse. Berliner Journal fr Soziologie, 12:87 – 108, 2002. [46] Christian Stegbauer. Freundschaft als beziehungsform: von der formalen soziologie zu harrison white. In Georg Stanitzek Natalie Binczek, editor, Strong ties / Weak ties. Freundschaftssemantik und Netzwerktheorie. Universittsverlag Winter, 2010. [47] Lee Rainie, John Horrigan, Barry Wellman, and Jeffrey Boase. The strength of internet ties. Available Online at http://www.pewinternet.org, 2006. [48] Bernadette Kneidinger. Facebook und Co. Eine soziologische Analyse von Interaktionsformen in Online Social Networks. Wiesbaden: VS, 2010. [49] Brinkmann and Seifert. ”face to interface”: Zum problem der vertrauenskonstitution im internet am beispiel von elektronischen auktionen. Zeitschrift fuer Soziologie, 30, 2001.
