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Distributed Learning of Distributions via Social Sampling  [PDF]
Anand D. Sarwate,Tara Javidi
Mathematics , 2013,
Abstract: A protocol for distributed estimation of discrete distributions is proposed. Each agent begins with a single sample from the distribution, and the goal is to learn the empirical distribution of the samples. The protocol is based on a simple message-passing model motivated by communication in social networks. Agents sample a message randomly from their current estimates of the distribution, resulting in a protocol with quantized messages. Using tools from stochastic approximation, the algorithm is shown to converge almost surely. Examples illustrate three regimes with different consensus phenomena. Simulations demonstrate this convergence and give some insight into the effect of network topology.
Providing Trustworthy Contributions via a Reputation Framework in Social Participatory Sensing Systems  [PDF]
Haleh Amintoosi,Salil S. Kanhere
Computer Science , 2013,
Abstract: Social participatory sensing is a newly proposed paradigm that tries to address the limitations of participatory sensing by leveraging online social networks as an infrastructure. A critical issue in the success of this paradigm is to assure the trustworthiness of contributions provided by participants. In this paper, we propose an application-agnostic reputation framework for social participatory sensing systems. Our framework considers both the quality of contribution and the trustworthiness level of participant within the social network. These two aspects are then combined via a fuzzy inference system to arrive at a final trust rating for a contribution. A reputation score is also calculated for each participant as a resultant of the trust ratings assigned to him. We adopt the utilization of PageRank algorithm as the building block for our reputation module. Extensive simulations demonstrate the efficacy of our framework in achieving high overall trust and assigning accurate reputation scores.
RankMerging: A supervised learning-to-rank framework to predict links in large social network  [PDF]
Lionel Tabourier,Daniel Faria Bernardes,Anne-Sophie Libert,Renaud Lambiotte
Computer Science , 2014,
Abstract: Uncovering unknown or missing links in social networks is a difficult task because of their sparsity and because links may represent different types of relationships, characterized by different structural patterns. In this paper, we define a simple yet efficient supervised learning-to-rank framework, called RankMerging, which aims at combining information provided by various unsupervised rankings. We illustrate our method on three different kinds of social networks and show that it substantially improves the performances of unsupervised metrics of ranking. We also compare it to other combination strategies based on standard methods. Finally, we explore various aspects of RankMerging, such as feature selection and parameter estimation and discuss its area of relevance: the prediction of an adjustable number of links on large networks.
Group Creativity in Learning Context: Understanding in a Social-Cultural Framework and Methodology  [PDF]
Chunfang Zhou, Lingling Luo
Creative Education (CE) , 2012, DOI: 10.4236/ce.2012.34062
Abstract: Recent studies have emphasized group creativity as a social-cultural conception, but they lack a focus on the relationship between group creativity and knowledge creation. This paper aims to build a framework for group creativity in a learning context which includes both theoretical understanding and empirical methodology. Thus, a literature review is led by the following questions: How has creativity theory been developed from individual to group level? From a social-cultural perspective, how can group creativity, knowledge creation, and their relationship be understood? And what methods have been employed to study group creativity? As the review demonstrates, creativity theory has been driven by new insights from recent sociology studies. Three focuses have been shaped from group creativity studies: 1) group creativity in context, 2) group-level creative synergy, and 3) strategies for developing group creativity. Individual knowledge is a potential resource for group creativity, and group creativity could be a driver of knowledge creation. Empirically, group creativity can be examined through both qualitative and quantitative approaches, which also calls for a creative combination of methodologies in future studies.
Automatic Surveillance and Control System Framework-DPS-KA-AT for Alleviating Disruptions of Social Media in Higher Learning Institutions  [PDF]
Kasaye Asres, Amin Tuni Gure, Durga Prasad Sharma
Journal of Computer and Communications (JCC) , 2020, DOI: 10.4236/jcc.2020.81001
Abstract: The worldwide change and transformations are taking place in socio-techno cultures. In the epicenter of all these Information and Communication Technologies (ICTs), the Internet is the backbone and paving salient communications and computations Medias like the emergence of social networking sites (SNSs). These SNSs are facilitating globalized entertainment, socialization, communications, and information sharing over hand-held electronic gazettes/mobiles like Facebook, Twitter, Instagram, Skype, and WhatsApp etc. The positive side of these SNSs is making the world a social village but apart from these positive aspects, there is another trait of multifold adversities/disruptions or negative effects which still have not been exposed and drawn attention. The remedial action for such adversities is needed to be designed and developed. The all age groups and genders are typically involved and resulting in wastage of time, money and peace of minds. The adverse effects of social media users in a Higher Learning Institutions are getting worse day-by-day. The prime aim of this research study is to design an automatic Surveillance System Framework for alleviation of the social media disruptions in these institutions. This framework aims to design and develop a surveillance system and access control guidelines for judiciously alleviating the misuse of social media. The study used MS form, Protopie, adobe XD and InVision for data collection, framework design and prototype development respectively. This research is an attempt to apply an explanatory and applied research design science approach using survey, interviews and technical observations-based primary data analytics. The study concluded with a cloud-based automatic surveillance, auto alerts and control system framework (DPS-KA-AT) and functionally validated by a system framework prototype. In the survey and interview, the 66% respondents’ response was “YES”, while 34% “NO” when enquired for the need assessment of the automatic surveillance and control system towards alleviation of the social media adversities or disruptions. This percentage indicates that the highest number of respondent or the highest number of higher learning institutions communities need an urgent automatic monitoring, surveillance and control system towards alleviation of such adversities/disruptions. The study concluded with a remark “a concrete and Automatic Surveillance and Control System Framework can be a great instrumental for minimizing the adversities of social media in higher learning institutions”.
Reaching Consensus via non-Bayesian Asynchronous Learning in Social Networks  [PDF]
Michal Feldman,Nicole Immorlica,Brendan Lucier,S. Matthew Weinberg
Computer Science , 2014,
Abstract: We study the outcomes of information aggregation in online social networks. Our main result is that networks with certain realistic structural properties avoid information cascades and enable a population to effectively aggregate information. In our model, each individual in a network holds a private, independent opinion about a product or idea, biased toward a ground truth. Individuals declare their opinions asynchronously, can observe the stated opinions of their neighbors, and are free to update their declarations over time. Supposing that individuals conform with the majority report of their neighbors, we ask whether the population will eventually arrive at consensus on the ground truth. We show that the answer depends on the network structure: there exist networks for which consensus is unlikely, or for which declarations converge on the incorrect opinion with positive probability. On the other hand, we prove that for networks that are sparse and expansive, the population will converge to the correct opinion with high probability.
In the Face (book) of Social Learning  [PDF]
Michail N. Giannakos,Patrick Mikalef
Computer Science , 2012,
Abstract: Social networks have risen to prominence over the last years as the predominant form of electronic interaction between individuals. In an attempt to harness the power of the large user base which they have managed to attract, this study proposes an e-learning prototype which integrates concepts of the social and semantic web. A selected set of services are deployed which have been scientifically proven to positively impact the learning process of users via electronic means. The integrability of these services into a social network platform application is visualized through an exploratory prototype. The Graphical User Interface (GUI) which is developed to implement these key features is in alignment with User-Centered principles. The designed prototype proves that a number of services can be integrated in a user-friendly application and can potentially serve to gain feedback regarding additional aspects that should be included.
Social Presence within the Community of Inquiry Framework  [cached]
David Annand
International Review of Research in Open and Distance Learning , 2011,
Abstract: The role of social presence as defined by the community of inquiry (CoI) framework is critiqued through a review of recent literature. Evidence is presented that questions the actual extent of knowledge co-construction that occurs in most higher education settings and therefore challenges the framework’s underlying assumption of the need for sustained, contiguous, two-way communication in higher-level online learning environments. The CoI framework has evolved from the description of a learning process within a social constructivist paradigm to an empirically testable construct in an objectivist paradigm. Related research results indicate that social presence does not impact cognitive presence in a meaningful way and that best teaching practices suggested by CoI-based studies are informed by objectivist, cognitively oriented learning theories. These suggest that higher-order cognition may be achieved through wide and varied combinations of learner–teacher, learner–content, and learner–learner interaction. Controlled studies can and should be undertaken to compare learning outcomes using sustained, contiguous, two-way communication to other learning models. To facilitate this, subcategories of social and teaching presences need to be revamped and analysis adjusted to separate processes that support explicitly group-based learning activities from those used by individual students.
An Integrated Framework for Learning and Reasoning  [PDF]
C. G. Giraud-Carrier,T. R. Martinez
Computer Science , 1995,
Abstract: Learning and reasoning are both aspects of what is considered to be intelligence. Their studies within AI have been separated historically, learning being the topic of machine learning and neural networks, and reasoning falling under classical (or symbolic) AI. However, learning and reasoning are in many ways interdependent. This paper discusses the nature of some of these interdependencies and proposes a general framework called FLARE, that combines inductive learning using prior knowledge together with reasoning in a propositional setting. Several examples that test the framework are presented, including classical induction, many important reasoning protocols and two simple expert systems.
Framework for Ubiquitous Social Networks  [PDF]
Atta ur Rehman Khan,Mazliza Othman,Abdul Nasir Khan,Imran Ali khan
Computer Science , 2013,
Abstract: This paper presents a novel framework for ubiquitous social networks (USNs). Instead of making virtual connections, on the basis of human social networks, an effort has been made to facilitate interactions among human social networks with the help of virtual social networks. The imperative domains that support ubiquitous social networks are highlighted and different scenarios are provided to project real world applications of proposed framework. Our proposed framework can provide preliminary foundations for creating ubiquitous social networks in true essence.
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