Web3Recommend: Decentralised recommendations with trust and relevance

Web3Recommend is a decentralized Social Recommender System implementation that enables Web3 Platforms on Android to generate recommendations that balance trust and relevance. Generating recommendations in decentralized networks is a non-trivial problem because these networks lack a global perspective due to the absence of a central authority. Further, decentralized networks are prone to Sybil Attacks in which a single malicious user can generate multiple fake or Sybil identities. Web3Recommend relies on a novel graph-based content recommendation design inspired by GraphJet, a recommendation system used in Twitter enhanced with MeritRank, a decentralized reputation scheme that provides Sybil-resistance to the system. By adding MeritRank's decay parameters to the vanilla Social Recommender Systems' personalized SALSA graph algorithm, we can provide theoretical guarantees against Sybil Attacks in the generated recommendations. Similar to GraphJet, we focus on generating real-time recommendations by only acting on recent interactions in the social network, allowing us to cater temporally contextual recommendations while keeping a tight bound on the memory usage in resource-constrained devices, allowing for a seamless user experience. As a proof-of-concept, we integrate our system with MusicDAO, an open-source Web3 music-sharing platform, to generate personalized, real-time recommendations. Thus, we provide the first Sybil-resistant Social Recommender System, allowing real-time recommendations beyond classic user-based collaborative filtering. The system is also rigorously tested with extensive unit and integration tests. Further, our experiments demonstrate the trust-relevance balance of recommendations against multiple adversarial strategies in a test network generated using data from real music platforms

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]

On social and technical aspects of managing mobile Ad-hoc communities

Soziale Software beschreibt eine Klasse von Anwendungen, die es Benutzern erlaubt ueber das Internet mit Freunden zu kommunizieren und Informationen auszutauschen. Mit zunehmender Leistungsfaehigkeit mobiler Prozessoren verwandeln sich Mobiltelefone in vollwertige Computer und eroeffnen neue Moeglichkeiten fuer die mobile Nutzung sozialer Software. Da Menschen Mobiltelefone haeufig bei sich fuehren, koennen vergleichbare mobile Anwendungen staerker auf ihre unmittelbare Umgebungssituation zugeschnitten werden. Moegliche Szenarien sind die Unterstuetzung realer Treffen und damit verbundenen Mitgliederinteraktionen. Client-Server-Plattformen, die dabei haeufig zum Einsatz kommen wurden allerdings nie fuer solche hochflexiblen Gruppensituationen konstruiert. Mobile Encounter Netzwerke (MENe) verprechen hier mehr Flexibilitaet. Ein MEN stellt eine mobiler Peer-to-Peer-Plattformen dar, das ueber ein kurzreichweitiges Funknetz betrieben wird. Mit diesem Netzwerk werden Beitraege ueber einen raeumlichen Diffusionsprozess von einem mobilen Endgeraet zum naechsten verbreitet. Das hat zwei entscheidende Vorteile: Zunaechst ist der direkte Nachrichtenaustausch besser geeignet zur Verbreitung von situationsspezifischer Information, da die Informationsrelevanz mit ihrer Entfehrnung abnimmt. Gleichzeitig koennen aber auch Inhalte, die fuer einen breiten Interessenkreis bestimmt sind ueber Mitglieder mit herausragenden Mobilitaetscharakteristik in weit entfernte Gebiete transportiert werden. Ein Nachteil ist jedoch der hohe Ressourcenverbrauch. Zur Loesung dieses Problems entwickeln wir ein Rahmenwerk zur Unterstuetzung mobiler ad-hoc Gruppen, das es uns erlaubt, Gruppensynergien gezielt auszunutzen. Dieses Rahmenwerk bietet Dienstleistungen zur Verwaltung der Gruppendynamik und zur Verbreitung von Inhalten an. Mittels soziale Netzwerkanalyse wird die technische Infrastruktur ohne notwendige Benutzereingriffe kontinuierlich an die reale Umgebungssituation angepasst. Dabei werden moegliche Beziehungen zwischen benachbarten Personen anhand frueher Begegnungen analysiert, spontane Gruppenbildungen mit Clusterverfahren identifiziert und jedem Gruppenmitglied eine geeignete Rolle durch eine Positionsanalyse zugewiesen. Eine Grundvorraussetzung fuer eine erfolgreiche Kooperation ist ein effizienter Wissensaustausch innerhalb einer Gemeinschaft. Wie die Small World-Theorie zeigt, koennen Menschen Wissen auch dann effizient verbreiten, wenn ihre Entscheidung nur auf lokaler Umgebungsinformation basiert. Verschiedene Forscher machten sich das zu nutze, indem sie kurze Verbreitungspfade durch eine Verkettung hochvernetzter Mitglieder innerhalb einer Gemeinschaft konstruierten. Allerdings laesst sich dieses Verfahren nicht einfach auf MENe uebertragen, da die Transferzeit im Gegensatz zu dem drahtgebundenen Internet beschraenkt ist. Unser Ansatz beruht daher, auf der von Reagan et al. vorgestellten Least Effort Transfer-Hypothese. Diese Hypothese besagt, dass Menschen Wissen nur dann weitergeben, wenn sich der Aufwand zur Informationsuebertragung innerhalb bestimmter Grenzen bewegt. Eine erfolgreiche Wissensuebertragung haengt in diesem Fall vom Hintergrundwissen aller Beteiligter ab, was wiederum von unterschiedlichen kognitiven und sozialen Faktoren abhaengt. Entsprechend leiten wir ein Diffusionsverfahren ab, dass in der Lage ist, Inhalte in verschiedene Kompexitaetstufen einzuteilen und Datenuebertragungen an die vorgefundene soziale Situation anzupassen. Mit einem Prototyp evaluieren wir die Machbarkeit der Gruppen- und Informationsmanagementkomponente unseres Rahmenwerkes. Da Laborexperimente keinen ausreichenden Aufschluss ueber Diffusionseigenschaften im groesseren Massstab geben koennen, simulieren wir die Beitragsdiffusion. Dazu dient uns eine Verkehrsimulation, bei der Agenten zusaetzlich mit aktivitaetsbezogenen, sozialen und territorialen Modellen erweitern werden. Um eine realitaetsnahe Simulation zu gewaehrleisten, werden diese Modelle in Uebereinstimmung mit verschiedenen Studien zum Stadtleben generiert. Der technische Uebertragungsprozess wird anhand der Ergebnisse einer vorangegangenen Prototypuntersuchung parametrisiert. Waehrend eines Simulationslaufes bewegen sich Agenten auf einem Stadtplan und sammeln Kontakt- und Beitragsdaten. Analysiert man anschliessend die Netzwerktopologie auf Small World-Eigenschaften, so findet man eine Netzstruktur mit einer ausgepraegten Neigung zum Clustering (Freundschaftsnetzwerke) und einer ueberdurschnittlichen kurzen Weglaenge. Offensichtlich reicht die Alltagsmobilitaet aus, um ausreichend viele Verknuepfungen zwischen Gemeinschaftmitgliedern zu bilden. Die nachfolgende Diffusionsanalyse zeigt, dass vergleichbare Reichweiten wie bei einem flutungsbasierten Ansatz erzielt werden, allerdings mit anfaenglichen Verzoegerungen. Da unser Verfahren bei einem Ortswechsel die Anzahl der Informationsuebermittler auf zentrale Gruppenmitglieder begrenzt, steht mehr Bandbreite fuer den Datenaustausch zur Verfuegung. Herkoemliche Mitglieder (ohne Leitungsaufgaben) tauschen Inhalte vornehmlich in zeitunkritschen Situationen aus. Das hat den positiven Nebeneffekt, dass im Cache erheblich weniger Kopien aussortiert werden muessen. Wechselt man waehrend der Simulation die Beitragskategorie so erkennt man, dass zeitabhaengige Inhalte besser ueber regelmaessige Kontakte und zeitunabhaengig Inhalte durch zufaellige Kontakte verbreitet werden. Eine abschliessende Precision-Recall Analyse zeigt, dass herkoemmliche Gruppenmitglieder eine bessere Genauigkeit (Precision), und zentrale Mitglieder eine bessere Trefferquote (Recall) im Vergleich zu traditionellen Ansaetzen besitzen. Eine Erklaerung dafuer ist, dass der von uns gewaehlte gruppenbasierte Cacheansatz zu weniger Saeuberungszyklen aller Gruppenmitglieder fuehrt und somit nachhaltiger ausgerichtet ist.Social software encompasses a range of software systems that allow users to interact and share data. This computer-mediated communication has become very popular with social networking sites like Facebook and Twitter. The evolvement of smart phones toward mobile computers opens new possibilities to use social software also in mobile usage scenarios. Since mobile phones are permanently carried by their owners, the support focus is, however, much stronger set on promoting and augmenting real group gatherings. Traditional client-server platforms are not flexible enough to support complex and dynamic human encounter behavior. Mobile encounter networks (MENs) which represent a mobile peer-to-peer platform on top of a short range wireless network promise better flexibility. MENs diffuse content from neighbor-to-neighbor in a spatial diffusion process. For physical group gatherings this is advantageous for two reasons. Direct device-to-device interactions encourage sharing of situation-dependent content. Moreover, content is not necessarily locked within friend groups and may trigger networking effects by reaching larger audiences through user mobility. One disadvantage is, however, the high resource usage. We develop a social software framework for mobile ad-hoc groups, which partly solves this problem. This framework supports services for the management of group dynamics and content diffusion within and between groups. Social network analysis as an inherent part of the framework is used to adapt internal community states continuously with real world encounter situations. We hereby qualify interpersonal relationships based on encounter and communication statistics, identify social groups through incremental clustering and assign diffusion roles through position analysis. To achieve efficient content dissemination we make use of social diffusion phenomena. Other researchers have experimented extensively with the small world model as it proofs that people transfer knowledge based on local knowledge but are still capable of diffusing it efficiently on a global scale. Their approach is often based on identifying short paths through member connectivity. However, this scenario is not applicable in MENs as transfer time is limited in contrast to the wired Internet. Our approach is therefore based on the least effort transfer theory. Following Reagan et al., who first postulated this hypothesis, people transfer knowledge only if the transfer effort is within specific limits, which depends on different social and cognitive factors. We derive routing mechanisms, which are capable of distinguishing between different content complexities and apply information about peer's expertise and social network to identify advantageous paths and content transfers options. We evaluate the feasibility of the group management and content transfer component with prototypes. Since labor settings do not allow to obtain information about large scale diffusion experiences, we also conduct a multi-agent simulation to evaluate the diffusion capabilities of the system. Experiences from an earlier prototype implementation have been used to quantify the technical routing process. To emulate realistic community life, we assigned to each agent an individual daily agenda, social contacts and territory preferences specified according to outcomes from different urban city life surveys. During the simulation agents move on a city map according to these models and collect contact and content specific data. Analyzing the network topology according to small world characteristics shows a structure with a high tendency for clustering (friend networks) and a short average path length. Daily urban mobility creates enough opportunities to form shortcuts through the community. Content diffusion analysis shows that our approach reaches a similar amount of peers as network flooding but with delays in the beginning. Since our approach artificially limits the number of intermediates to central community peers more bandwidth is available during traveling and more content can be transferred as in the case of the flooding approach. Ordinary peers seem to have significantly fewer content replications if an unlimited cache is assumed proofing that our mechanism is more efficient. By varying the content type used during the simulation we recognize that time dependent content is better disseminated through frequent contacts and time independent content through random contacts. Performing a precision-recall analysis on peers caches shows that ordinary peers gain an overall better context precision, and central peers a better community recall. One explanation is that the shared cache approach leads to fewer content replacements in the cache as for instance the least recently used cache strategy

Applications of blockchain technology in marketing : a systematic review of marketing technology companies

Given the emerging nature of integrating Blockchain Technology (BCT) into several business fields concerning the interaction between companies and their customers, this study aims to investigate the applications of BCT in marketing through an accurate procedure of locating, selecting and analyzing existing companies using BCT in marketing. A sample that consists of 800 companies was identified using web-scraping methods. The data set was collected from initial coin offerings (ICO) websites as well as from an existing, older landscape of applications. The data set was then intensively analyzed in order to be categorized into five fields of marketing technology. Advertising and ecommerce outgrew the other fields of social & relationship, content & experience and data in absolute numbers, revealing the focus of practitioners in the past as well as gaps for the future. The authors provided future directions for researchers on and development of tools to systematically generate knowledge and improve the application of BCT and the work of practitioners in marketing

Design of a Recommender System for Participatory Media Built on a Tetherless Communication Infrastructure

We address the challenge of providing low-cost, universal access of useful information to people in different parts of the globe. We achieve this by following two strategies. First, we focus on the delivery of information through computerized devices and prototype new methods for making that delivery possible in a secure, low-cost, and universal manner. Second, we focus on the use of participatory media, such as blogs, in the context of news related content, and develop methods to recommend useful information that will be of interest to users. To achieve the first goal, we have designed a low-cost wireless system for Internet access in rural areas, and a smartphone-based system for the opportunistic use of WiFi connectivity to reduce the cost of data transfer on multi-NIC mobile devices. Included is a methodology for secure communication using identity based cryptography. For the second goal of identifying useful information, we make use of sociological theories regarding social networks in mass-media to develop a model of how participatory media can offer users effective news-related information. We then use this model to design a recommender system for participatory media content that pushes useful information to people in a personalized fashion. Our algorithms provide an order of magnitude better performance in terms of recommendation accuracy than other state-of-the-art recommender systems. Our work provides some fundamental insights into the design of low-cost communication systems and the provision of useful messages to users in participatory media through a multi-disciplinary approach. The result is a framework that efficiently and effectively delivers information to people in remote corners of the world

Enhancing trustability in MMOGs environments

Massively Multiplayer Online Games (MMOGs; e.g., World of Warcraft), virtual worlds (VW; e.g., Second Life), social networks (e.g., Facebook) strongly demand for more autonomic, security, and trust mechanisms in a way similar to humans do in the real life world. As known, this is a difficult matter because trusting in humans and organizations depends on the perception and experience of each individual, which is difficult to quantify or measure. In fact, these societal environments lack trust mechanisms similar to those involved in humans-to-human interactions. Besides, interactions mediated by compute devices are constantly evolving, requiring trust mechanisms that keep the pace with the developments and assess risk situations. In VW/MMOGs, it is widely recognized that users develop trust relationships from their in-world interactions with others. However, these trust relationships end up not being represented in the data structures (or databases) of such virtual worlds, though they sometimes appear associated to reputation and recommendation systems. In addition, as far as we know, the user is not provided with a personal trust tool to sustain his/her decision making while he/she interacts with other users in the virtual or game world. In order to solve this problem, as well as those mentioned above, we propose herein a formal representation of these personal trust relationships, which are based on avataravatar interactions. The leading idea is to provide each avatar-impersonated player with a personal trust tool that follows a distributed trust model, i.e., the trust data is distributed over the societal network of a given VW/MMOG. Representing, manipulating, and inferring trust from the user/player point of view certainly is a grand challenge. When someone meets an unknown individual, the question is “Can I trust him/her or not?”. It is clear that this requires the user to have access to a representation of trust about others, but, unless we are using an open source VW/MMOG, it is difficult —not to say unfeasible— to get access to such data. Even, in an open source system, a number of users may refuse to pass information about its friends, acquaintances, or others. Putting together its own data and gathered data obtained from others, the avatar-impersonated player should be able to come across a trust result about its current trustee. For the trust assessment method used in this thesis, we use subjective logic operators and graph search algorithms to undertake such trust inference about the trustee. The proposed trust inference system has been validated using a number of OpenSimulator (opensimulator.org) scenarios, which showed an accuracy increase in evaluating trustability of avatars. Summing up, our proposal aims thus to introduce a trust theory for virtual worlds, its trust assessment metrics (e.g., subjective logic) and trust discovery methods (e.g., graph search methods), on an individual basis, rather than based on usual centralized reputation systems. In particular, and unlike other trust discovery methods, our methods run at interactive rates.MMOGs (Massively Multiplayer Online Games, como por exemplo, World of Warcraft), mundos virtuais (VW, como por exemplo, o Second Life) e redes sociais (como por exemplo, Facebook) necessitam de mecanismos de confiança mais autónomos, capazes de assegurar a segurança e a confiança de uma forma semelhante à que os seres humanos utilizam na vida real. Como se sabe, esta não é uma questão fácil. Porque confiar em seres humanos e ou organizações depende da percepção e da experiência de cada indivíduo, o que é difícil de quantificar ou medir à partida. Na verdade, esses ambientes sociais carecem dos mecanismos de confiança presentes em interacções humanas presenciais. Além disso, as interacções mediadas por dispositivos computacionais estão em constante evolução, necessitando de mecanismos de confiança adequados ao ritmo da evolução para avaliar situações de risco. Em VW/MMOGs, é amplamente reconhecido que os utilizadores desenvolvem relações de confiança a partir das suas interacções no mundo com outros. No entanto, essas relações de confiança acabam por não ser representadas nas estruturas de dados (ou bases de dados) do VW/MMOG específico, embora às vezes apareçam associados à reputação e a sistemas de reputação. Além disso, tanto quanto sabemos, ao utilizador não lhe é facultado nenhum mecanismo que suporte uma ferramenta de confiança individual para sustentar o seu processo de tomada de decisão, enquanto ele interage com outros utilizadores no mundo virtual ou jogo. A fim de resolver este problema, bem como os mencionados acima, propomos nesta tese uma representação formal para essas relações de confiança pessoal, baseada em interacções avatar-avatar. A ideia principal é fornecer a cada jogador representado por um avatar uma ferramenta de confiança pessoal que segue um modelo de confiança distribuída, ou seja, os dados de confiança são distribuídos através da rede social de um determinado VW/MMOG. Representar, manipular e inferir a confiança do ponto de utilizador/jogador, é certamente um grande desafio. Quando alguém encontra um indivíduo desconhecido, a pergunta é “Posso confiar ou não nele?”. É claro que isto requer que o utilizador tenha acesso a uma representação de confiança sobre os outros, mas, a menos que possamos usar uma plataforma VW/MMOG de código aberto, é difícil — para não dizer impossível — obter acesso aos dados gerados pelos utilizadores. Mesmo em sistemas de código aberto, um número de utilizadores pode recusar partilhar informações sobre seus amigos, conhecidos, ou sobre outros. Ao juntar seus próprios dados com os dados obtidos de outros, o utilizador/jogador representado por um avatar deve ser capaz de produzir uma avaliação de confiança sobre o utilizador/jogador com o qual se encontra a interagir. Relativamente ao método de avaliação de confiança empregue nesta tese, utilizamos lógica subjectiva para a representação da confiança, e também operadores lógicos da lógica subjectiva juntamente com algoritmos de procura em grafos para empreender o processo de inferência da confiança relativamente a outro utilizador. O sistema de inferência de confiança proposto foi validado através de um número de cenários Open-Simulator (opensimulator.org), que mostrou um aumento na precisão na avaliação da confiança de avatares. Resumindo, a nossa proposta visa, assim, introduzir uma teoria de confiança para mundos virtuais, conjuntamente com métricas de avaliação de confiança (por exemplo, a lógica subjectiva) e em métodos de procura de caminhos de confiança (com por exemplo, através de métodos de pesquisa em grafos), partindo de uma base individual, em vez de se basear em sistemas habituais de reputação centralizados. Em particular, e ao contrário de outros métodos de determinação do grau de confiança, os nossos métodos são executados em tempo real