523 research outputs found

    Recommending investors for crowdfunding projects

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    To bring their innovative ideas to market, those embarking in new ventures have to raise money, and, to do so, they have often resorted to banks and venture capitalists. Nowadays, they have an additional option: that of crowdfunding. The name refers to the idea that funds come from a network of people on the Internet who are passionate about supporting others' projects. One of the most popular crowdfunding sites is Kickstarter. In it, creators post descriptions of their projects and advertise them on social media sites (mainly Twitter), while investors look for projects to support. The most common reason for project failure is the inability of founders to connect with a sufficient number of investors, and that is mainly because hitherto there has not been any automatic way of matching creators and investors. We thus set out to propose different ways of recommending investors found on Twitter for specific Kickstarter projects. We do so by conducting hypothesis-driven analyses of pledging behavior and translate the corresponding findings into different recommendation strategies. The best strategy achieves, on average, 84% of accuracy in predicting a list of potential investors' Twitter accounts for any given project. Our findings also produced key insights about the whys and wherefores of investors deciding to support innovative efforts

    Y-Comm: a global architecture for heterogeneous networking.

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    In the near future mobile devices with several interfaces will become commonplace. Most of the peripheral networks using the Internet will therefore employ wireless technology. To provide support for these devices, this paper proposes a new framework which encompasses the functions of both peripheral and core networks. The framework is called Y-Comm and is defined in a layered manner like the OSI model

    Human-Data Interaction: The Human Face of the Data-Driven Society

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    The increasing generation and collection of personal data has created a complex ecosystem, often collaborative but sometimes combative, around companies and individuals engaging in the use of these data. We propose that the interactions between these agents warrants a new topic of study: Human-Data Interaction (HDI). In this paper we discuss how HDI sits at the intersection of various disciplines, including computer science, statistics, sociology, psychology and behavioural economics. We expose the challenges that HDI raises, organised into three core themes of legibility, agency and negotiability, and we present the HDI agenda to open up a dialogue amongst interested parties in the personal and big data ecosystems

    An architectural framework for heterogeneous networking.

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    The growth over the last decade in the use of wireless networking devices has been explosive. Soon many devices will have multiple network interfaces, each with very different characteristics. We believe that a framework that encapsulates the key challenges of heterogeneous networking is required. Like a map clearly helps one to plan a journey, a framework is needed to help us move forward in this unexplored area. The approach taken here is similar to the OSImodel in which tightly defined layers are used to specify functionality, allowing a modular approach to the extension of systems and the interchange of their components, whilst providing a model that is more oriented to heterogeneity and mobility

    Partisan sharing: Facebook evidence and societal consequences

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    The hypothesis of selective exposure assumes that people seek out information that supports their views and eschew information that conflicts with their beliefs, and that has negative consequences on our society. Few researchers have recently found counter evidence of selective exposure in social media: users are exposed to politically diverse articles. No work has looked at what happens after exposure, particularly how individuals react to such exposure, though. Users might well be exposed to diverse articles but share only the partisan ones. To test this, we study partisan sharing on Facebook: the tendency for users to predominantly share like-minded news articles and avoid conflicting ones. We verified four main hypotheses. That is, whether partisan sharing: 1) exists at all; 2) changes across individuals (e.g., depending on their interest in politics); 3) changes over time (e.g., around elections); and 4) changes depending on perceived importance of topics. We indeed find strong evidence for partisan sharing. To test whether it has any consequence in the real world, we built a web application for BBC viewers of a popular political program, resulting in a controlled experiment involving more than 70 individuals. Based on what they share and on survey data, we find that partisan sharing has negative consequences: distorted perception of reality. However, we do also find positive aspects of partisan sharing: it is associated with people who are more knowledgeable about politics and engage more with it as they are more likely to vote in the general elections.Jisun An was supported in part by the Google European Doctoral Fellowship in Social Computing

    FLICK: developing and running application-specific network services

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    Data centre networks are increasingly programmable, with application-specific network services proliferating, from custom load-balancers to middleboxes providing caching and aggregation. Developers must currently implement these services using traditional low-level APIs, which neither support natural operations on application data nor provide efficient performance isolation. We describe FLICK, a framework for the programming and execution of application-specific network services on multi-core CPUs. Developers write network services in the FLICK language, which offers high-level processing constructs and application-relevant data types. FLICK programs are translated automatically to efficient, parallel task graphs, implemented in C++ on top of a user-space TCP stack. Task graphs have bounded resource usage at runtime, which means that the graphs of multiple services can execute concurrently without interference using cooperative scheduling. We evaluate FLICK with several services (an HTTP load-balancer, a Memcached router and a Hadoop data aggregator), showing that it achieves good performance while reducing development effort

    Turning down the lamp: Software specialisation for the cloud

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    © USENIX Workshop on Hot Topics in Cloud Computing, HotCloud 2010.All right reserved. The wide availability of cloud computing offers an unprecedented opportunity to rethink how we construct applications. The cloud is currently mostly used to package up existing software stacks and operating systems (e.g. LAMP) for scaling out websites. We instead view the cloud as a stable hardware platform, and present a programming framework which permits applications to be constructed to run directly on top of it without intervening software layers. Our prototype (dubbed Mirage) is unashamedly academic; it extends the Objective Caml language with storage extensions and a custom run-time to emit binaries that execute as a guest operating system under Xen. Mirage applications exhibit significant performance speedups for I/O and memory handling versus the same code running under Linux/Xen. Our results can be generalised to offer insight into improving more commonly used languages such as PHP, Python and Ruby, and we discuss lessons learnt and future directions

    Exploiting contextual handover information for versatile services in NGN environments.

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    Users in ubiquitous and pervasive computing environments will be much more empowered in ways to access and to control their navigation. Handover, the vital event in which a user changes the attachment point in a Next Generation Network (NGN), is an important occasion and the conditions and environment in which it is executed can offer relevant information for businesses. This paper describes the capabilities of a platform which intends to exploit contextual handover information offering a rich environment that can be used by access and content providers for building innovative context-aware multi-provided services. Based on ontologies, the technique not only eases the building of versatile services but also provides a comprehensive source of information both for enriching user navigation in the network as well as for the improvement of the provider’s relationship with their customers

    Jitsu: Just-in-time summoning of unikernel

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    Network latency is a problem for all cloud services. It can be mitigated by moving computation out of remote datacenters by rapidly instantiating local services near the user. This requires an embedded cloud platform on which to deploy multiple applications securely and quickly. We present Jitsu, a new Xen toolstack that satisfies the demands of secure multi-tenant isolation on resource-constrained embedded ARM devices. It does this by using unikernels: lightweight, compact, single address space, memory-safe virtual machines (VMs) written in a high-level language. Using fast shared memory channels, Jitsu provides a directory service that launches unikernels in response to network traffic and masks boot latency. Our evaluation shows Jitsu to be a power-efficient and responsive platform for hosting cloud services in the edge network while preserving the strong isolation guarantees of a type-1 hypervisor.The research leading to these results received funding from the European Union’s Seventh Framework Programme FP7/2007–2013 under the Trilogy 2 project (grant agreement no. 317756), and the User Centric Networking project, (grant agreement no. 611001), and the Defense Advanced Research Projects Agency (DARPA) and the Air Force Research Laboratory (AFRL), under contract FA8750-11-C-0249.This is the author accepted manuscript. The final version is available from USENIX via https://www.usenix.org/conference/nsdi15/technical-sessions/presentation/madhavapedd

    Personal data management with the databox: What's inside the box?

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    We are all increasingly the subjects of data collection and processing systems that use data generated both about and by us to provide and optimise a wide range of services. Means for others to collect and process data that concerns each of us -- often referred to possessively as "your data" -- are only increasing with the long-heralded advent of the Internet of Things just the latest example. As a result, means to enable personal data management is generally recognised as a pressing societal issue. We have previously proposed that one such means might be realised by the Databox, a collection of physical and cloud-hosted software components that provide for an individual data subject to manage, log and audit access to their data by other parties. In this paper we elaborate on this proposal, describing the software architecture we are developing, and the current status of a prototype implementation. We conclude with a brief discussion of Databox's limitations
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